Papers

The following preprints are provided here to allow for a deeper view of our research work, as well as to promote the rapid dissemination of research results. Please consider, on the other hand, that these preprints can differ from their published version in ways that may not be entirely negligible, and for this reason we recommend you to refer to the published version whenever they have to be used or cited.
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2024

D'Agostino, A., Garbazza, C., Malpetti, D., Azzimonti, L., Mangili, F., Stein, H., del Giudice, R., Cicolin, A., Cirignotta, F., Manconi, M., Aquilino, D., Baiardi, S., Bianconcini, A., Canevini, M., Cicolin, A., Cirignotta, F., D'Agostino, A., Giudice, R.D., Fanti, V., Filippakos, F., Fior, G., Fonti, C., Furia, F., Gambini, O., Garbazza, C., Giordano, A., Giordano, B., Manconi, M., Marconi, A.M., Martini, A., Mondini, S., Piazza, N., Raimondo, E., Riccardi, S., Rizzo, N., Santoro, R., Serrati, C., Simonazzi, G., Stein, H., Zambrelli, E. (2024). Optimal risk and diagnosis assessment strategies in perinatal depression: a machine learning approach from the life-ON study cohort. Psychiatry Research 332, 115687.

Optimal risk and diagnosis assessment strategies in perinatal depression: a machine learning approach from the life-ON study cohort

@ARTICLE{malpetti2024a,
   title = {Optimal risk and diagnosis assessment strategies in perinatal depression: a machine learning approach from the life-{ON} study cohort},
   journal = {Psychiatry Research},
   volume = {332},
   author = {D'Agostino, A. and Garbazza, C. and Malpetti, D. and Azzimonti, L. and Mangili, F. and Stein, H. and del Giudice, R. and Cicolin, A. and Cirignotta, F. and Manconi, M. and Aquilino, D. and Baiardi, S. and Bianconcini, A. and Canevini, M. and Cicolin, A. and Cirignotta, F. and D'Agostino, A. and Giudice, R.D. and Fanti, V. and Filippakos, F. and Fior, G. and Fonti, C. and Furia, F. and Gambini, O. and Garbazza, C. and Giordano, A. and Giordano, B. and Manconi, M. and Marconi, A.M. and Martini, A. and Mondini, S. and Piazza, N. and Raimondo, E. and Riccardi, S. and Rizzo, N. and Santoro, R. and Serrati, C. and Simonazzi, G. and Stein, H. and Zambrelli, E.},
   pages = {115687},
   year = {2024},
   doi = {10.1016/j.psychres.2023.115687},
   url = {}
}
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Antonucci, A., Piqué, G., Zaffalon, M. (2024). Zero-shot causal graph extrapolation from text via LLMs. In First XAI4Sci Workshop on Explainable Machine Learning for Sciences (@AAAI '24).

Zero-shot causal graph extrapolation from text via LLMs

@INPROCEEDINGS{antonucci2023a,
   title = {Zero-shot causal graph extrapolation from text via {LLMs}},
   booktitle = {First {XAI4Sci} Workshop on Explainable Machine Learning for Sciences ({@AAAI} '24)},
   author = {Antonucci, A. and Piqu\'e, G. and Zaffalon, M.},
   year = {2024},
   doi = {},
   url = {http://arxiv.org/abs/2312.14670}
}
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Manconi, M., van der Gaag, L.C., Mangili, F., Garbazza, C., Riccardi, S., Cajochen, C., Mondini, S., Furia, F., Zambrelli, E., Baiardi, S., Giordano, A., Rizzo, N., Fonti, C., Viora, E., D'Agostino, A., Cicolin, A., Cirignotta, F., Aquilino, D., Barassi, A., del Giudice, R., Fior, G., Gambini, O., Giordano, B., Martini, A., Serrati, C., Stefanelli, R., Scarone, S., Canevini, M., Fanti, V., Stein, H., Marconi, A.M., Raimondo, E., Viglietta, E., Santoro, R., Simonazzi, G., Bianconcini, A., Meani, F., Piazza, N., Filippakos, F., Gyr, T. (2024). Sleep and sleep disorders during pregnancy and postpartum: The Life-ON study. Sleep Medicine 113, pp. 41–48.

Sleep and sleep disorders during pregnancy and postpartum: The Life-ON study

@ARTICLE{mangili2023a,
   title = {Sleep and sleep disorders during pregnancy and postpartum: {T}he {L}ife-{ON} study},
   journal = {Sleep Medicine},
   volume = {113},
   author = {Manconi, M. and van der Gaag, L.C. and Mangili, F. and Garbazza, C. and Riccardi, S. and Cajochen, C. and Mondini, S. and Furia, F. and Zambrelli, E. and Baiardi, S. and Giordano, A. and Rizzo, N. and Fonti, C. and Viora, E. and D'Agostino, A. and Cicolin, A. and Cirignotta, F. and Aquilino, D. and Barassi, A. and del Giudice, R. and Fior, G. and Gambini, O. and Giordano, B. and Martini, A. and Serrati, C. and Stefanelli, R. and Scarone, S. and Canevini, M. and Fanti, V. and Stein, H. and Marconi, A.M. and Raimondo, E. and Viglietta, E. and Santoro, R. and Simonazzi, G. and Bianconcini, A. and Meani, F. and Piazza, N. and Filippakos, F. and Gyr, T.},
   pages = {41--48},
   year = {2024},
   doi = {doi.org/10.1016/j.sleep.2023.10.021},
   url = {}
}
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Zaffalon, M., Antonucci, A., Cabañas, R., Huber, D., Azzimonti, D. (2024). Efficient computation of counterfactual bounds. International Journal of Approximate Reasoning, 109111.

Efficient computation of counterfactual bounds

@ARTICLE{zaffalon2023b,
   title = {Efficient computation of counterfactual bounds},
   journal = {International Journal of Approximate Reasoning},
   author = {Zaffalon, M. and Antonucci, A. and Caba\~nas, R. and Huber, D. and Azzimonti, D.},
   pages = {109111},
   year = {2024},
   doi = {10.1016/j.ijar.2023.109111},
   url = {}
}
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Zambon, L., Agosto, A., Giudici, P., Corani, G. (2024). Properties of the reconciled distributions for Gaussian and count forecasts. International Journal of Forecasting.

Properties of the reconciled distributions for Gaussian and count forecasts

@ARTICLE{zambon2024b,
   title = {Properties of the reconciled distributions for {G}aussian and count forecasts},
   journal = {International Journal of Forecasting},
   author = {Zambon, L. and Agosto, A. and Giudici, P. and Corani, G.},
   year = {2024},
   doi = {10.1016/j.ijforecast.2023.12.004},
   url = {}
}
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Zambon, L., Azzimonti, D., Corani, G. (2024). Efficient probabilistic reconciliation of forecasts for real-valued and count time series. Statistics and Computing 32(1), 21.

Efficient probabilistic reconciliation of forecasts for real-valued and count time series

@ARTICLE{zambon2024a,
   title = {Efficient probabilistic reconciliation of forecasts for real-valued and count time series},
   journal = {Statistics and Computing},
   volume = {32},
   author = {Zambon, L. and Azzimonti, D. and Corani, G.},
   number = {1},
   pages = {21},
   year = {2024},
   doi = {10.1007/s11222-023-10343-y},
   url = {}
}
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2023

Adorni, G., Mangili, F., Piatti, A., Bonesana, C., Antonucci, A. (2023). Rubric-based learner modelling via noisy gates Bayesian networks for computational thinking skills assessment. Journal of Communications Software and System 19(1), pp. 52–64.

Rubric-based learner modelling via noisy gates Bayesian networks for computational thinking skills assessment

@ARTICLE{Adorni2023,
   title = {Rubric-based learner modelling via noisy gates {B}ayesian networks for computational thinking skills assessment},
   journal = {Journal of Communications Software and System},
   volume = {19},
   author = {Adorni, G. and Mangili, F. and Piatti, A. and Bonesana, C. and Antonucci, A.},
   number = {1},
   pages = {52--64},
   year = {2023},
   doi = {10.24138/jcomss-2022-0169},
   url = {}
}
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Allan, J., Mangili, F., Derboni, M., Gisler, L., Hainoun, A., Rizzoli, A., Ventriglia, L., Sulzer, M. (2023). A semantic data framework to support data-driven demand forecasting. In 2600(2), 022001.

A semantic data framework to support data-driven demand forecasting

@INPROCEEDINGS{mangili2023b,
   title = {A semantic data framework to support data-driven demand forecasting},
   journal = {Journal of Physics: Conference Series},
   volume = {2600},
   author = {Allan, J. and Mangili, F. and Derboni, M. and Gisler, L. and Hainoun, A. and Rizzoli, A. and Ventriglia, L. and Sulzer, M.},
   number = {2},
   pages = {022001},
   year = {2023},
   doi = {10.1088/1742-6596/2600/2/022001},
   url = {}
}
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Barcellona, S., Cannelli, L., Colnago, S., Laurano, C., Piegari, L. (2023). Cycle aging effect on lithium-ion battery resistance: a machine learning approach. In 2023 IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), pp. 389–394.

Cycle aging effect on lithium-ion battery resistance: a machine learning approach

@INPROCEEDINGS{cannelli2023b,
   title = {Cycle aging effect on lithium-ion battery resistance: a machine learning approach},
   booktitle = {2023 {IEEE} International Conference on Metrology for {eXtended} Reality, Artificial Intelligence and Neural Engineering ({MetroXRAINE})},
   author = {Barcellona, S. and Cannelli, L. and Colnago, S. and Laurano, C. and Piegari, L.},
   pages = {389--394},
   year = {2023},
   doi = {10.1109/MetroXRAINE58569.2023.10405749},
   url = {}
}
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Benavoli, A., Azzimonti, D., Piga, D. (2023). Learning choice functions with Gaussian processes. In Evans, Robin J., Shpitser, Ilya (Eds),, Proceedings of Machine Learning Research 216, PMLR, pp. 141–151.

Learning choice functions with Gaussian processes

@INPROCEEDINGS{azzimonti2023b,
   title = {Learning choice functions with {G}aussian processes},
   editor = {Evans, Robin J. and Shpitser, Ilya},
   publisher = {PMLR},
   series = {Proceedings of Machine Learning Research},
   volume = {216},
   author = {Benavoli, A. and Azzimonti, D. and Piga, D.},
   pages = {141--151},
   year = {2023},
   doi = {},
   url = {https://proceedings.mlr.press/v216/benavoli23a.html}
}
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Benavoli, A., Azzimonti, D., Piga, D. (2023). Bayesian optimization for choice data. In Proceedings of the Companion Conference on Genetic and Evolutionary Computation, ACM, pp. 2272–2279.

Bayesian optimization for choice data

@INPROCEEDINGS{azzimontid2023a,
   title = {Bayesian optimization for choice data},
   publisher = {ACM},
   booktitle = {Proceedings of the Companion Conference on Genetic and Evolutionary Computation},
   author = {Benavoli, A. and Azzimonti, D. and Piga, D.},
   pages = {2272--2279},
   year = {2023},
   doi = {10.1145/3583133.3596324},
   url = {}
}
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Benavoli, A., Facchini, A., Zaffalon, M. (2023). Closure operators, classifiers and desirability. In Quaeghebeur, E., Miranda, E., Montes, I., Vantaggi, B. (Eds), ISIPTA '23: Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications, PLMR 215, JMLR, pp. 25–36.

Closure operators, classifiers and desirability

@INPROCEEDINGS{benavoli2023a,
   title = {Closure operators, classifiers and desirability},
   editor = {Quaeghebeur, E. and Miranda, E. and Montes, I. and Vantaggi, B.},
   publisher = {JMLR},
   series = {PLMR},
   volume = {215},
   booktitle = {{ISIPTA} '23: Proceedings of the Thirteenth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Benavoli, A. and Facchini, A. and Zaffalon, M.},
   pages = {25--36},
   year = {2023},
   doi = {},
   url = {https://proceedings.mlr.press/v215/benavoli23a.html}
}
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Bernasconi, A., Zanga, A., Lucas, P.J.F., Scutari, M., Stella, F. (2023). Towards a transportable causal network model based on observational healthcare data. In Proceedings of the 2nd Workshop on Artificial Intelligence for Healthcare, 22nd International Conference of the Italian Association for Artificial Intelligence (AIxIA 2023).

Towards a transportable causal network model based on observational healthcare data

@INPROCEEDINGS{scutari2023c,
   title = {Towards a transportable causal network model based on observational healthcare data},
   booktitle = {Proceedings of the 2nd Workshop on Artificial Intelligence for Healthcare, 22nd International Conference of the Italian Association for Artificial Intelligence ({AIxIA} 2023)},
   author = {Bernasconi, A. and Zanga, A. and Lucas, P.J.F. and Scutari, M. and Stella, F.},
   year = {2023},
   doi = {},
   url = {https://ceur-ws.org/Vol-3578}
}
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Bregoli, A., Rathsman, K., Scutari, M., Stella, F., Mogesen, S.W. (2023). Analyzing complex systems with cascades using continuous time Bayesian networks. In Proceedings of the 30th International Symposium on Temporal Representation and Reasoning (TIME23), pp. 8:1–8:21.

Analyzing complex systems with cascades using continuous time Bayesian networks

@INPROCEEDINGS{scutari2023b,
   title = {Analyzing complex systems with cascades using continuous time {B}ayesian networks},
   booktitle = {Proceedings of the 30th International Symposium on Temporal Representation and Reasoning ({TIME23})},
   author = {Bregoli, A. and Rathsman, K. and Scutari, M. and Stella, F. and Mogesen, S.W.},
   pages = {8:1--8:21},
   year = {2023},
   doi = {},
   url = {https://paperswithcode.com/paper/analyzing-complex-systems-with-cascades-using}
}
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Briganti, G., Scutari, M., McNally, R.J. (2023). A tutorial on Bayesian networks for psychopathology researchers. Psychological Methods 28(4), pp. 947–961.

A tutorial on Bayesian networks for psychopathology researchers

@ARTICLE{scutari2023h,
   title = {A tutorial on {B}ayesian networks for psychopathology researchers},
   journal = {Psychological Methods},
   volume = {28},
   author = {Briganti, G. and Scutari, M. and McNally, R.J.},
   number = {4},
   pages = {947--961},
   year = {2023},
   doi = {doi.org/10.1037/met0000479},
   url = {}
}
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Cannelli, L., Nuti, G., Sala, M., Szehr, O. (2023). Hedging using reinforcement learning: contextual k-armed bandit versus Q-learning. The Journal of Finance and Data Science 9, 100101.

Hedging using reinforcement learning: contextual k-armed bandit versus Q-learning

@ARTICLE{szehr2023c,
   title = {Hedging using reinforcement learning: contextual k-armed bandit versus {Q}-learning},
   journal = {The Journal of Finance and Data Science},
   publisher = {Elsevier},
   volume = {9},
   author = {Cannelli, L. and Nuti, G. and Sala, M. and Szehr, O.},
   pages = {100101},
   year = {2023},
   doi = {10.1016/j.jfds.2023.100101},
   url = {}
}
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Cannelli, L., Zhu, M., Farina, F., Bemporad, A., Piga, D. (2023). Multi-agent active learning for distributed black-box optimization. IEEE Control Systems Letters 7, pp. 1488–1493.

Multi-agent active learning for distributed black-box optimization

@ARTICLE{cannelli2023a,
   title = {Multi-agent active learning for distributed black-box optimization},
   journal = {{IEEE} Control Systems Letters},
   volume = {7},
   author = {Cannelli, L. and Zhu, M. and Farina, F. and Bemporad, A. and Piga, D.},
   pages = {1488--1493},
   year = {2023},
   doi = {10.1109/LCSYS.2023.3270347},
   url = {}
}
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Casanova, A., Benavoli, A., Zaffalon, M. (2023). Nonlinear desirability as a linear classification problem. International Journal of Approximate Reasoning 152, pp. 1–32.

Nonlinear desirability as a linear classification problem

@ARTICLE{casanova2023a,
   title = {Nonlinear desirability as a linear classification problem},
   journal = {International Journal of Approximate Reasoning},
   volume = {152},
   author = {Casanova, A. and Benavoli, A. and Zaffalon, M.},
   pages = {1--32},
   year = {2023},
   doi = {10.1016/j.ijar.2022.10.008},
   url = {}
}
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Cellina, F., Simão, J.V., Mangili, F., Vermes, N., Granato, P. (2023). Sustainable mobility persuasion via smartphone apps: Lessons from a Swiss case study on how to design point-based rewarding systems. Travel Behaviour and Society 31, pp. 178–188.

Sustainable mobility persuasion via smartphone apps: Lessons from a Swiss case study on how to design point-based rewarding systems

@ARTICLE{mangili2023,
   title = {Sustainable mobility persuasion via smartphone apps: {L}essons from a {S}wiss case study on how to design point-based rewarding systems},
   journal = {Travel Behaviour and Society},
   volume = {31},
   author = {Cellina, F. and Sim\~ao, J.V. and Mangili, F. and Vermes, N. and Granato, P.},
   pages = {178--188},
   year = {2023},
   doi = {10.1016/j.tbs.2022.12.001},
   url = {}
}
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Corani, G., Azzimonti, D., Rubattu, N. (2023). Probabilistic reconciliation of count time series. International Journal of Forecasting.

Probabilistic reconciliation of count time series

@ARTICLE{CORANI2023a,
   title = {Probabilistic reconciliation of count time series},
   journal = {International Journal of Forecasting},
   author = {Corani, G. and Azzimonti, D. and Rubattu, N.},
   year = {2023},
   doi = {10.1016/j.ijforecast.2023.04.003},
   url = {}
}
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Corradini, F., Flammini, F., Antonucci, A. (2023). Probabilistic modelling for trustworthy artificial intelligence in drone-supported autonomous wheelchairs. In Proceedings of the First International Symposium on Trustworthy Autonomous Systems, Association for Computing Machinery.

Probabilistic modelling for trustworthy artificial intelligence in drone-supported autonomous wheelchairs

@INPROCEEDINGS{corradini2023a,
   title = {Probabilistic modelling for trustworthy artificial intelligence in drone-supported autonomous wheelchairs},
   publisher = {Association for Computing Machinery},
   booktitle = {Proceedings of the First International Symposium on Trustworthy Autonomous Systems},
   author = {Corradini, F. and Flammini, F. and Antonucci, A.},
   year = {2023},
   doi = {10.1145/3597512.3599716},
   url = {}
}
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Gupta, A., Mejari, M., Falcone, P., Piga, D. (2023). Computation of parameter dependent robust invariant sets for lpv models with guaranteed performance. Automatica 151, 110920.

Computation of parameter dependent robust invariant sets for lpv models with guaranteed performance

@ARTICLE{mejari2023a,
   title = {Computation of parameter dependent robust invariant sets for lpv models with guaranteed performance},
   journal = {Automatica},
   volume = {151},
   author = {Gupta, A. and Mejari, M. and Falcone, P. and Piga, D.},
   pages = {110920},
   year = {2023},
   doi = {10.1016/j.automatica.2023.110920},
   url = {https://www.sciencedirect.com/science/article/pii/S0005109823000705}
}
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Huber, D., Chen, Y., Antonucci, A., Darwiche, A., Zaffalon, M. (2023). Tractable bounding of counterfactual queries by knowledge compilation. In The 6th Workshop on Tractable Probabilistic Modeling.

Tractable bounding of counterfactual queries by knowledge compilation

@INPROCEEDINGS{huber2023a,
   title = {Tractable bounding of counterfactual queries by knowledge compilation},
   booktitle = {The 6th Workshop on Tractable Probabilistic Modeling},
   author = {Huber, D. and Chen, Y. and Antonucci, A. and Darwiche, A. and Zaffalon, M.},
   year = {2023},
   doi = {},
   url = {https://openreview.net/forum?id=kPb6CQZo93}
}
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Kanjirangat, V., Antonucci, A. (2023). Edge labelling in narrative knowledge graphs. In Proceedings of Text2Story — Sixth Workshop on Narrative Extraction From Texts held in conjunction with the 45th European Conference on Information Retrieval (ECIR 2023) 3370, CEUR Workshop Proceedings, pp. 135–142.

Edge labelling in narrative knowledge graphs

@INPROCEEDINGS{kanjirangat2023a,
   title = {Edge labelling in narrative knowledge graphs},
   publisher = {CEUR Workshop Proceedings},
   volume = {3370},
   booktitle = {Proceedings of {Text2Story} — Sixth Workshop on Narrative Extraction From Texts {h}eld in {c}onjunction {w}ith the 45th European Conference on Information Retrieval ({ECIR} 2023)},
   author = {Kanjirangat, V. and Antonucci, A.},
   pages = {135--142},
   year = {2023},
   doi = {},
   url = {https://ceur-ws.org/Vol-3370/}
}
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Liew, B.X.W., Palacios-Ceña, M., Scutari, M., Fuensalida-Novo, S., Guerrero-Peral, A., Ordás-Bandera, C., Pareja, J.A., & Fernández-de-Las-Peñas, C. (2023). Path analysis models integrating psychological, psycho-physical and clinical variables in individuals with tension-type headache. The Journal of Pain 24(3), pp. 426–436.

Path analysis models integrating psychological, psycho-physical and clinical variables in individuals with tension-type headache

@ARTICLE{scutari2023i,
   title = {Path analysis models integrating psychological, psycho-physical and clinical variables in individuals with tension-type headache},
   journal = {The Journal of Pain},
   volume = {24},
   author = {Liew, B.X.W. and Palacios-Ce\~na, M. and Scutari, M. and Fuensalida-Novo, S. and Guerrero-Peral, A. and Ord\'as-Bandera, C. and Pareja, J.A. and & Fern\'andez-de-Las-Pe\~nas, C.},
   number = {3},
   pages = {426--436},
   year = {2023},
   doi = {10.1016/j.jpain.2022.10.003},
   url = {}
}
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Liew, B.X.W., Hartvigsen, J., Scutari, M., Kongsted, A. (2023). Data-driven network analysis identified subgroup-specific low back pain pathways: a cross-sectional GLA:D Back study. Journal of Clinical Epidemiology 153, pp. 66–77.

Data-driven network analysis identified subgroup-specific low back pain pathways: a cross-sectional GLA:D Back study

@ARTICLE{scutari2023f,
   title = {Data-driven network analysis identified subgroup-specific low back pain pathways: a cross-sectional {GLA}:{D} {B}ack study},
   journal = {Journal of Clinical Epidemiology},
   publisher = {Elsevier},
   volume = {153},
   author = {Liew, B.X.W. and Hartvigsen, J. and Scutari, M. and Kongsted, A.},
   pages = {66--77},
   year = {2023},
   doi = {10.1016/j.jclinepi.2022.11.010 },
   url = {}
}
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Maggiolo, M., Szehr, O. (2023). Overfitting in portfolio optimization. Journal of Risk Model Validation 17(3), pp. 1–33.

Overfitting in portfolio optimization

@ARTICLE{szehr2023a,
   title = {Overfitting in portfolio optimization},
   journal = {Journal of Risk Model Validation},
   volume = {17},
   author = {Maggiolo, M. and Szehr, O.},
   number = {3},
   pages = {1--33},
   year = {2023},
   doi = {10.21314/JRMV.2023.005},
   url = {}
}
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Mejari, M., Forgione, M., Piga, D. (2023). Variational autoencoder for the identification of piecewise models. In 56(2), pp. 4055–4060.

Variational autoencoder for the identification of piecewise models

@INPROCEEDINGS{mejari2023c,
   title = {Variational autoencoder for the identification of piecewise models},
   journal = {{IFAC}-{PapersOnLine}},
   volume = {56},
   author = {Mejari, M. and Forgione, M. and Piga, D.},
   number = {2},
   pages = {4055--4060},
   year = {2023},
   doi = {10.1016/j.ifacol.2023.10.1728},
   url = {}
}
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Mejari, M., Gupta, A., Piga, D. (2023). Data-driven computation of robust invariant sets and gain-scheduled controllers for linear parameter-varying systems. IEEE Control Systems Letters 7, pp. 3355–3360.

Data-driven computation of robust invariant sets and gain-scheduled controllers for linear parameter-varying systems

@ARTICLE{mejari2023d,
   title = {Data-driven computation of robust invariant sets and gain-scheduled controllers for linear parameter-varying systems},
   journal = {{IEEE} Control Systems Letters},
   volume = {7},
   author = {Mejari, M. and Gupta, A. and Piga, D.},
   pages = {3355--3360},
   year = {2023},
   doi = {10.1109/LCSYS.2023.3329291},
   url = {}
}
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Mejari, M., Piga, D. (2023). Direct identification of continuous-time linear switched state-space models. In 56(2), pp. 4210–4215.

Direct identification of continuous-time linear switched state-space models

@INPROCEEDINGS{mejari2023b,
   title = {Direct identification of continuous-time linear switched state-space models},
   journal = {{IFAC}-{PapersOnLine}},
   volume = {56},
   author = {Mejari, M. and Piga, D.},
   number = {2},
   pages = {4210--4215},
   year = {2023},
   doi = {10.1016/j.ifacol.2023.10.1773},
   url = {}
}
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Miranda, E., Zaffalon, M. (2023). Nonlinear desirability theory. International Journal of Approximate Reasoning 154, pp. 176–199.

Nonlinear desirability theory

@ARTICLE{miranda2023a,
   title = {Nonlinear desirability theory},
   journal = {International Journal of Approximate Reasoning},
   volume = {154},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {176--199},
   year = {2023},
   doi = {10.1016/j.ijar.2022.12.015},
   url = {}
}
Download
Mitrović, S., Frisone, F., Gupta, S., Lucifora, C., Čarapić, D., Schillaci, C., Di Giovanni, S., Singh, A. (2023). Annotating panic in social media using active learning, transformers and domain knowledge. 2023 IEEE International Conference on Data Mining Workshops (ICDMW).

Annotating panic in social media using active learning, transformers and domain knowledge

@ARTICLE{mitrovic2023a,
   title = {Annotating panic in social media using active learning, transformers and domain knowledge},
   journal = {2023 {IEEE} International Conference on Data Mining Workshops ({ICDMW})},
   publisher = {IEEE},
   author = {Mitrović, S. and Frisone, F. and Gupta, S. and Lucifora, C. and Čarapić, D. and Schillaci, C. and Di Giovanni, S. and Singh, A.},
   year = {2023},
   doi = {},
   url = {http://xhealth.one/dmmd}
}
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Rubattu, N., Maroni, G., Corani, G. (2023). Electricity load and peak forecasting: feature engineering, probabilistic LightGBM and temporal hierarchies. In Ifrim, G., Tavenard, R., Bagnall, A., Schaefer, P., Malinowski, S., Guyet, T., Lemaire, V. (Eds), Advanced Analytics and Learning on Temporal Data, Springer Nature Switzerland, pp. 276–292.

Electricity load and peak forecasting: feature engineering, probabilistic LightGBM and temporal hierarchies

@INPROCEEDINGS{corani2023b,
   title = {Electricity load and peak forecasting: feature engineering, probabilistic {LightGBM} and temporal hierarchies},
   editor = {Ifrim, G. and Tavenard, R. and Bagnall, A. and Schaefer, P. and Malinowski, S. and Guyet, T. and Lemaire, V.},
   publisher = {Springer Nature Switzerland},
   booktitle = {Advanced Analytics and Learning on Temporal Data},
   author = {Rubattu, N. and Maroni, G. and Corani, G.},
   pages = {276--292},
   year = {2023},
   doi = {10.1007/978-3-031-49896-1_18},
   url = {}
}
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Schürch, M., Azzimonti, D., Benavoli, A., Zaffalon, M. (2023). Correlated product of experts for sparse Gaussian process regression. Machine Learning 112, pp. 1411–1432.

Correlated product of experts for sparse Gaussian process regression

@ARTICLE{schurch2023,
   title = {Correlated product of experts for sparse {G}aussian process regression},
   journal = {Machine Learning},
   publisher = {Springer},
   volume = {112},
   author = {Sch\"urch, M. and Azzimonti, D. and Benavoli, A. and Zaffalon, M.},
   pages = {1411--1432},
   year = {2023},
   doi = {10.1007/s10994-022-06297-3},
   url = {}
}
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Scutari, M., Malvestio, M. (2023). Developing and running machine learning software: machine learning operations (MLOps). Wiley StatsRef: Statistics Reference Online, pp. 1–8.

Developing and running machine learning software: machine learning operations (MLOps)

@ARTICLE{scutari2023e,
   title = {Developing and running machine learning software: machine learning operations ({MLOps})},
   journal = {Wiley {StatsRef}: Statistics Reference Online},
   publisher = {John Wiley & Sons, Ltd},
   author = {Scutari, M. and Malvestio, M.},
   pages = {1--8},
   year = {2023},
   doi = {10.1002/9781118445112.stat08455},
   url = {}
}
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Scutari, M., Malvestio, M. (2023). Machine learning software and pipelines. Wiley StatsRef: Statistics Reference Online, pp. 1–6.

Machine learning software and pipelines

@ARTICLE{scutari2023g,
   title = {Machine learning software and pipelines},
   journal = {Wiley {StatsRef}: Statistics Reference Online},
   author = {Scutari, M. and Malvestio, M.},
   pages = {1--6},
   year = {2023},
   doi = {10.1002/9781118445112.stat08454},
   url = {}
}
Download
Selmonaj, A., Szehr, O., Del Rio, G., Antonucci, A., Schneider, A., Rüegsegger, M. (2023). Hierarchical multi-agent reinforcement learning for air combat maneuvering. In , IEEE.

Hierarchical multi-agent reinforcement learning for air combat maneuvering

@INPROCEEDINGS{selmonaj2023a,
   title = {Hierarchical multi-agent reinforcement learning for air combat maneuvering},
   journal = {Proceedings of the 22nd International on Machine Learning and Applications},
   publisher = {IEEE},
   author = {Selmonaj, A. and Szehr, O. and Del Rio, G. and Antonucci, A. and Schneider, A. and R\"uegsegger, M.},
   year = {2023},
   doi = {},
   url = {https://www.icmla-conference.org/icmla23/}
}
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Szehr, O., Maggiolo, M. (2023). Hedging of financial derivative contracts via Monte Carlo tree search. Journal of Computational Finance 27(2), pp. 47–80.

Hedging of financial derivative contracts via Monte Carlo tree search

@ARTICLE{szehr2023b,
   title = {Hedging of financial derivative contracts via {M}onte {C}arlo tree search},
   journal = {Journal of Computational Finance},
   volume = {27},
   author = {Szehr, O. and Maggiolo, M.},
   number = {2},
   pages = {47--80},
   year = {2023},
   doi = {10.21314/JCF.2023.009},
   url = {}
}
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Termine, A., Antonucci, A., Facchini, A. (2023). Machine learning explanations by surrogate causal models (MaLESCaMo). In Longo, L. (Ed), Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the First World Conference on eXplainable Artificial Intelligence (xAI-2023) 3554, CEUR Workshop Proceedings, pp. 59–64.

Machine learning explanations by surrogate causal models (MaLESCaMo)

@INPROCEEDINGS{termine2023a,
   title = {Machine learning explanations by surrogate causal models ({MaLESCaMo})},
   editor = {Longo, L.},
   publisher = {CEUR Workshop Proceedings},
   volume = {3554},
   booktitle = {Joint Proceedings of the {xAI}-2023 Late-{b}reaking Work, Demos and Doctoral Consortium {c}o-{l}ocated {w}ith the First World Conference on {eXplainable} Artificial Intelligence ({xAI}-2023)},
   author = {Termine, A. and Antonucci, A. and Facchini, A.},
   pages = {59--64},
   year = {2023},
   doi = {},
   url = {https://ceur-ws.org/Vol-3554}
}
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Termine, A., Antonucci, A., Primiero, G., Facchini, A. (2023). Imprecise probabilistic model checking for stochastic multi-agent systems. SN Computer Science 4(443).

Imprecise probabilistic model checking for stochastic multi-agent systems

@ARTICLE{termine2023b,
   title = {Imprecise probabilistic model checking for stochastic multi-agent systems},
   journal = {{SN} Computer Science},
   volume = {4},
   author = {Termine, A. and Antonucci, A. and Primiero, G. and Facchini, A.},
   number = {443},
   year = {2023},
   doi = {10.1007/s42979-023-01817-x},
   url = {}
}
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Zaffalon, M., Antonucci, A., Cabañas, R., Huber, D. (2023). Approximating counterfactual bounds while fusing observational, biased and randomised data sources. International Journal of Approximate Reasoning 162, 109023.

Approximating counterfactual bounds while fusing observational, biased and randomised data sources

@ARTICLE{zaffalon2023a,
   title = {Approximating counterfactual bounds while fusing observational, biased and randomised data sources},
   journal = {International Journal of Approximate Reasoning},
   volume = {162},
   author = {Zaffalon, M. and Antonucci, A. and Caba\~nas, R. and Huber, D.},
   pages = {109023},
   year = {2023},
   doi = {10.1016/j.ijar.2023.109023},
   url = {}
}
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Zanga, A., Bernasconi, A., Lucas, P.J.F., Pijnenborg, H., Rejinen, C., Scutari, M., Stella, F. (2023). Causal discovery with missing data in a multicentric clinical study. In Juarez, Jose M., Marcos, Mar, Stiglic, Gregor, Tucker, Allan (Eds), Proceedings of the 21st International Conference on Artificial Intelligence in Medicine (AIME23), Springer Nature Switzerland, pp. 40–44.

Causal discovery with missing data in a multicentric clinical study

@INPROCEEDINGS{scutari2023d,
   title = {Causal discovery with missing data in a multicentric clinical study},
   editor = {Juarez, Jose M. and Marcos, Mar and Stiglic, Gregor and Tucker, Allan},
   publisher = {Springer Nature Switzerland},
   booktitle = {Proceedings of the 21st International Conference on Artificial Intelligence in Medicine ({AIME23})},
   author = {Zanga, A. and Bernasconi, A. and Lucas, P.J.F. and Pijnenborg, H. and Rejinen, C. and Scutari, M. and Stella, F.},
   pages = {40--44},
   year = {2023},
   doi = {10.1007/978-3-031-34344-5_5},
   url = {}
}
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2022

Allante, L., Korfiati, A., Androutsos, L., Stojceski, F., Bompotas, A., Giannikos, I., Raftopoulos, C., Malavolta, M., Grasso, G., Mavroudi, S., Theofilatos, K., Piga, D., Deriu, M. (2022). Toward a general and interpretable umami taste predictor using a multi-objective machine learning approach. Scientific Reports, Nature Publishing Group 12(1), 21735.

Toward a general and interpretable umami taste predictor using a multi-objective machine learning approach

@ARTICLE{piga2022a,
   title = {Toward a general and interpretable umami taste predictor using a multi-objective machine learning approach},
   journal = {Scientific Reports, Nature Publishing Group},
   volume = {12},
   author = {Allante, L. and Korfiati, A. and Androutsos, L. and Stojceski, F. and Bompotas, A. and Giannikos, I. and Raftopoulos, C. and Malavolta, M. and Grasso, G. and Mavroudi, S. and Theofilatos, K. and Piga, D. and Deriu, M.},
   number = {1},
   pages = {21735},
   year = {2022},
   doi = {10.1038/s41598-022-25935-3},
   url = {}
}
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Antonucci, A., Mangili, F., Bonesana, C., Adorni, G. (2022). Intelligent tutoring systems by Bayesian nets with noisy gates. In 35.

Intelligent tutoring systems by Bayesian nets with noisy gates

@INPROCEEDINGS{antonucci2022a,
   title = {Intelligent tutoring systems by {B}ayesian nets with noisy gates},
   journal = {The International {FLAIRS} Conference Proceedings},
   volume = {35},
   author = {Antonucci, A. and Mangili, F. and Bonesana, C. and Adorni, G.},
   year = {2022},
   doi = {10.32473/flairs.v35i.130692},
   url = {}
}
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Azzimonti, L., Corani, G., Scutari, M. (2022). A bayesian hierarchical score for structure learning from related data sets. International Journal of Approximate Reasoning 142, pp. 248–265.

A bayesian hierarchical score for structure learning from related data sets

@ARTICLE{azzimonti2022a,
   title = {A bayesian hierarchical score for structure learning from related data sets},
   journal = {International Journal of Approximate Reasoning},
   volume = {142},
   author = {Azzimonti, L. and Corani, G. and Scutari, M.},
   pages = {248--265},
   year = {2022},
   doi = {10.1016/j.ijar.2021.11.013},
   url = {}
}
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Benavoli, A., Facchini, A., Zaffalon, M. (2022). Quantum indistinguishability through exchangeability. International Journal of Approximate Reasoning 151, pp. 389–412.

Quantum indistinguishability through exchangeability

@ARTICLE{benavoli2022a,
   title = {Quantum indistinguishability through exchangeability},
   journal = {International Journal of Approximate Reasoning},
   volume = {151},
   author = {Benavoli, A. and Facchini, A. and Zaffalon, M.},
   pages = {389--412},
   year = {2022},
   doi = {10.1016/j.ijar.2022.10.003},
   url = {}
}
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Bianchi, F., Piroddi, L., Bemporad, A., Halasz, G., Villani, M., Piga, D. (2022). Active preference-based optimization for human-in-the-loop feature selection. European Journal of Control 66, 100647.

Active preference-based optimization for human-in-the-loop feature selection

@ARTICLE{piga2022c,
   title = {Active preference-based optimization for human-in-the-loop feature selection},
   journal = {European Journal of Control},
   volume = {66},
   author = {Bianchi, F. and Piroddi, L. and Bemporad, A. and Halasz, G. and Villani, M. and Piga, D.},
   pages = {100647},
   year = {2022},
   doi = {10.1016/j.ejcon.2022.100647},
   url = {}
}
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Casanova, A., Kohlas, J., Zaffalon, M. (2022). Information algebras in the theory of imprecise probabilities. International Journal of Approximate Reasoning 142, pp. 383–416.

Information algebras in the theory of imprecise probabilities

@ARTICLE{casanova2022a,
   title = {Information algebras in the theory of imprecise probabilities},
   journal = {International Journal of Approximate Reasoning},
   volume = {142},
   author = {Casanova, A. and Kohlas, J. and Zaffalon, M.},
   pages = {383--416},
   year = {2022},
   doi = {10.1016/j.ijar.2021.12.017},
   url = {}
}
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Casanova, A., Kohlas, J., Zaffalon, M. (2022). Information algebras in the theory of imprecise probabilities, an extension. International Journal of Approximate Reasoning 150, pp. 311–336.

Information algebras in the theory of imprecise probabilities, an extension

@ARTICLE{casanova2022b,
   title = {Information algebras in the theory of imprecise probabilities, an extension},
   journal = {International Journal of Approximate Reasoning},
   volume = {150},
   author = {Casanova, A. and Kohlas, J. and Zaffalon, M.},
   pages = {311--336},
   year = {2022},
   doi = {10.1016/j.ijar.2022.09.003},
   url = {}
}
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Delfanti, G., Cortesi, F., Perini, A., Antonini, G., Azzimonti, L., de Lalla, C., Garavaglia, C., Squadrito, M.L., Fedeli, M., Consonni, M., Sesana, S., Re, F., Shen, H., Dellabona, P., Casorati, G. (2022). TCR-engineered iNKT cells induce robust antitumor response by dual targeting cancer and suppressive myeloid cells. Science Immunology 7(74), eabn6563.

TCR-engineered iNKT cells induce robust antitumor response by dual targeting cancer and suppressive myeloid cells

@ARTICLE{azzimonti2022b,
   title = {{TCR}-engineered {iNKT} cells induce robust antitumor response by dual targeting cancer and suppressive myeloid cells},
   journal = {Science Immunology},
   volume = {7},
   author = {Delfanti, G. and Cortesi, F. and Perini, A. and Antonini, G. and Azzimonti, L. and de Lalla, C. and Garavaglia, C. and Squadrito, M.L. and Fedeli, M. and Consonni, M. and Sesana, S. and Re, F. and Shen, H. and Dellabona, P. and Casorati, G.},
   number = {74},
   pages = {eabn6563},
   year = {2022},
   doi = {10.1126/sciimmunol.abn6563},
   url = {}
}
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Delucchi, M., Spinner, G.R., Scutari, M., Bijlenga, P., Morel, S., Friedrich, C.M., Furrer, R., Hirsch, S. (2022). Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors. Computers in Biology and Medicine 147, 105740.

Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors

@ARTICLE{scutari22c,
   title = {Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors},
   journal = {Computers in Biology and Medicine},
   volume = {147},
   author = {Delucchi, M. and Spinner, G.R. and Scutari, M. and Bijlenga, P. and Morel, S. and Friedrich, C.M. and Furrer, R. and Hirsch, S.},
   pages = {105740},
   year = {2022},
   doi = {10.1016/j.compbiomed.2022.105740},
   url = {}
}
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Držajić, D., Wiessner, M., Maradia, U., Piga, D. (2022). Virtual operators with self and transfer learning ability in EDM. Procedia CIRP 113, pp. 17–22.

Virtual operators with self and transfer learning ability in EDM

@ARTICLE{piga2022e,
   title = {Virtual operators with self and transfer learning ability in {EDM}},
   journal = {Procedia {CIRP}},
   volume = {113},
   author = {Držajić, D. and Wiessner, M. and Maradia, U. and Piga, D.},
   pages = {17--22},
   year = {2022},
   doi = {10.1016/j.procir.2022.09.113},
   url = {}
}
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Formenti, A., Bucca, G., Shahid, A.A., Piga, D., Roveda, L. (2022). Improved Impedance/Admittance switching controller for the interaction with a variable stiffness environment. Complex Engineering Systems 2(3), 12.

Improved Impedance/Admittance switching controller for the interaction with a variable stiffness environment

@ARTICLE{Roveda2022f,
   title = {Improved {Impedance/Admittance} switching controller for the interaction with a variable stiffness environment},
   journal = {Complex Engineering Systems},
   volume = {2},
   author = {Formenti, A. and Bucca, G. and Shahid, A.A. and Piga, D. and Roveda, L.},
   number = {3},
   pages = {12},
   year = {2022},
   doi = {10.20517/ces.2022.16},
   url = {}
}
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Hiel, S., Nicolaers, L., Ortega Vazquez, C., Mitrović, S., Baesens, B., De Weerdt, J. (2022). Evaluation of joint modeling techniques for node embedding and community detection on graphs. In 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

Evaluation of joint modeling techniques for node embedding and community detection on graphs

@INPROCEEDINGS{sandra2022a,
   title = {Evaluation of joint modeling techniques for node embedding and community detection on graphs},
   booktitle = {2022 {IEEE/ACM} International Conference on Advances in Social Networks Analysis and Mining ({ASONAM})},
   author = {Hiel, S. and Nicolaers, L. and Ortega Vazquez, C. and Mitrović, S. and Baesens, B. and De Weerdt, J.},
   year = {2022},
   doi = {},
   url = {}
}
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Kronauer, S., Mavkov, B., Mejari, M., Piga, D., Jaques, F., d'Amario, R., Di Campli, R., Nasciuti, A. (2022). Data-driven statistical analysis for discharge position prediction on Wire EDM. Procedia CIRP 113, pp. 143–148.

Data-driven statistical analysis for discharge position prediction on Wire EDM

@ARTICLE{mejari2022b,
   title = {Data-driven statistical analysis for discharge position prediction on {W}ire {EDM}},
   journal = {Procedia {CIRP}},
   volume = {113},
   author = {Kronauer, S. and Mavkov, B. and Mejari, M. and Piga, D. and Jaques, F. and d'Amario, R. and Di Campli, R. and Nasciuti, A.},
   pages = {143--148},
   year = {2022},
   doi = {10.1016/j.procir.2022.09.122},
   url = {}
}
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Liew, B.X.W., de-la-Llave-Rincón, A.I., Scutari, M., Arias-Buría, J.L., Cook, C.E., Cleland, J., Fernández-de-las-Peñas, C. (2022). Do short-term effects predict long-term improvements in women who receive manual therapy or surgery for carpal tunnel syndrome? A Bayesian network analysis of a randomized clinical trial . Physical Therapy 102(4), pzac015.

Do short-term effects predict long-term improvements in women who receive manual therapy or surgery for carpal tunnel syndrome? A Bayesian network analysis of a randomized clinical trial

@ARTICLE{scutari22b,
   title = {Do short-term effects predict long-term improvements in women who receive manual therapy or surgery for carpal tunnel syndrome? A {B}ayesian network analysis of a randomized clinical trial },
   journal = {Physical Therapy},
   volume = {102},
   author = {Liew, B.X.W. and de-la-Llave-Rinc\'on, A.I. and Scutari, M. and Arias-Bur\'ia, J.L. and Cook, C.E. and Cleland, J. and Fern\'andez-de-las-Pe\~nas, C.},
   number = {4},
   pages = {pzac015},
   year = {2022},
   doi = {10.1093/ptj/pzac015},
   url = {}
}
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Malavolta, M., Pallante, L., Mavkov, B., Stojceski, F., Grasso, G., Korfiati, A., Mavroudi, S., Kalogeras, A., Alexakos, C., Martos, V., Daria, A., Giacomo, D.B.P.D., Theofilatos, K., Deriu, M. (2022). A survey on computational taste predictors. European Food Research and Technology 248(9), pp. 2215–2235.

A survey on computational taste predictors

@ARTICLE{piga2022d,
   title = {A survey on computational taste predictors},
   journal = {European Food Research and Technology},
   volume = {248},
   author = {Malavolta, M. and Pallante, L. and Mavkov, B. and Stojceski, F. and Grasso, G. and Korfiati, A. and Mavroudi, S. and Kalogeras, A. and Alexakos, C. and Martos, V. and Daria, A. and Giacomo, D.B.P.D. and Theofilatos, K. and Deriu, M.},
   number = {9},
   pages = {2215--2235},
   year = {2022},
   doi = {10.1007/s00217-022-04044-5},
   url = {}
}
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Malpetti, D., Bellisario, A., Macchiavello, C. (2022). Multipartite entanglement in qudit hypergraph states. Journal of Physics A: Mathematical and Theoretical 55(41), 415301.

Multipartite entanglement in qudit hypergraph states

@ARTICLE{malpetti2022b,
   title = {Multipartite entanglement in qudit hypergraph states},
   journal = {Journal of Physics A: Mathematical and Theoretical},
   editor = {IOP Publishing},
   volume = {55},
   author = {Malpetti, D. and Bellisario, A. and Macchiavello, C.},
   number = {41},
   pages = {415301},
   year = {2022},
   doi = {10.1088/1751-8121/ac91b2},
   url = {}
}
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Mangili, F., Adorni, G., Piatti, A., Bonesana, C., Antonucci, A. (2022). Modelling assessment rubrics through Bayesian networks: a pragmatic approach. Proceedings of 2022 International Conference on Software, Telecommunications and Computer Networks (SoftCOM).

Modelling assessment rubrics through Bayesian networks: a pragmatic approach

@ARTICLE{mangili2022a,
   title = {Modelling assessment rubrics through {B}ayesian networks: a pragmatic approach},
   journal = {Proceedings of 2022 International Conference on Software, Telecommunications and Computer Networks ({SoftCOM})},
   publisher = {IEEE},
   author = {Mangili, F. and Adorni, G. and Piatti, A. and Bonesana, C. and Antonucci, A.},
   year = {2022},
   doi = {},
   url = {}
}
Download
Maroni, G., Pallante, L., Di Benedetto, G., Deriu, M.A., Piga, D., Grasso, G. (2022). Informed classification of sweeteners/bitterants compounds via explainable machine learning. Current Research in Food Science 5, pp. 2270–2280.

Informed classification of sweeteners/bitterants compounds via explainable machine learning

@ARTICLE{maroni2022a,
   title = {Informed classification of sweeteners/bitterants compounds via explainable machine learning},
   journal = {Current Research in Food Science},
   volume = {5},
   author = {Maroni, G. and Pallante, L. and Di Benedetto, G. and Deriu, M.A. and Piga, D. and Grasso, G.},
   pages = {2270--2280},
   year = {2022},
   doi = {10.1016/j.crfs.2022.11.014},
   url = {}
}
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Mejari, M., Mavkov, B., Forgione, M., Piga, D. (2022). Direct identification of continuous-time lpv state-space models via an integral architecture. Automatica 142, 110407.

Direct identification of continuous-time lpv state-space models via an integral architecture

@ARTICLE{mejari2022c,
   title = {Direct identification of continuous-time lpv state-space models via an integral architecture},
   journal = {Automatica},
   volume = {142},
   author = {Mejari, M. and Mavkov, B. and Forgione, M. and Piga, D.},
   pages = {110407},
   year = {2022},
   doi = {https://doi.org/10.1016/j.automatica.2022.110407},
   url = {https://www.sciencedirect.com/science/article/pii/S0005109822002606}
}
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Mejari, M., Piga, D. (2022). Maximum—a posteriori estimation of linear time-invariant state-space models via efficient monte-carlo sampling. ASME Letters in Dynamic Systems and Control 2(1).

Maximum—a posteriori estimation of linear time-invariant state-space models via efficient monte-carlo sampling

@ARTICLE{mejari2022a,
   title = {Maximum—a posteriori estimation of linear time-invariant state-space models via efficient monte-carlo sampling},
   journal = {{ASME} Letters in Dynamic Systems and Control},
   volume = {2},
   author = {Mejari, M. and Piga, D.},
   number = {1},
   year = {2022},
   doi = {10.1115/1.4051491},
   url = {}
}
Download
Mitrović, S., Kanjirangat, V. (2022). Enhancing BERT performance with contextual valence shifters for panic detection in COVID-19 tweets. In The 6th International Conference on Natural Language Processing and Information Retrieval (NLPIR 2022).

Enhancing BERT performance with contextual valence shifters for panic detection in COVID-19 tweets

@INPROCEEDINGS{mitrovic2022b,
   title = {Enhancing {BERT} performance with contextual valence shifters for panic detection in {COVID}-19 tweets},
   edition = {To appear},
   booktitle = {The 6th International Conference on Natural Language Processing and Information Retrieval ({NLPIR} 2022)},
   author = {Mitrović, S. and Kanjirangat, V.},
   year = {2022},
   doi = {},
   url = {}
}
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Paolillo, A., Nava, M., Piga, D., Giusti, A. (2022). Visual servoing with geometrically interpretable neural perception. In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5300–5306.

Visual servoing with geometrically interpretable neural perception

@INPROCEEDINGS{piga2022b,
   title = {Visual servoing with geometrically interpretable neural perception},
   booktitle = {2022 {IEEE/RSJ} International Conference on Intelligent Robots and Systems ({IROS})},
   author = {Paolillo, A. and Nava, M. and Piga, D. and Giusti, A.},
   pages = {5300--5306},
   year = {2022},
   doi = {10.1109/IROS47612.2022.9982163},
   url = {}
}
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Pesenti, M., Gandolla, M., Folcio, C., Ouyang, S., Rovelli, L., Covarrubias, M., Roveda, L. (2022). Sensor-based task ergonomics feedback for a passive low-back exoskeleton. In Miesenberger, K., Kouroupetroglou, G., Mavrou, K., Manduchi, R., Covarrubias Rodriguez, M., Penáz, P. (Eds), Computers Helping People with Special Needs, Springer International Publishing, pp. 403–410.

Sensor-based task ergonomics feedback for a passive low-back exoskeleton

@INPROCEEDINGS{Roveda2022h,
   title = {Sensor-based task ergonomics feedback for a passive low-back exoskeleton},
   editor = {Miesenberger, K. and Kouroupetroglou, G. and Mavrou, K. and Manduchi, R. and Covarrubias Rodriguez, M. and Pen\'az, P.},
   publisher = {Springer International Publishing},
   booktitle = {Computers Helping People {w}ith Special Needs},
   author = {Pesenti, M. and Gandolla, M. and Folcio, C. and Ouyang, S. and Rovelli, L. and Covarrubias, M. and Roveda, L.},
   pages = {403--410},
   year = {2022},
   doi = {10.1007/978-3-031-08645-8_47},
   url = {}
}
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Pesenti, M., Gandolla, M., Pedrocchi, A., Roveda, L. (2022). A backbone-tracking passive exoskeleton to reduce the stress on the low-back: proof of concept study. In 2022 International Conference on Rehabilitation Robotics (ICORR), pp. 1–6.

A backbone-tracking passive exoskeleton to reduce the stress on the low-back: proof of concept study

@INPROCEEDINGS{Roveda2022j,
   title = {A backbone-tracking passive exoskeleton to reduce the stress on the low-back: proof of concept study},
   booktitle = {2022 International Conference on Rehabilitation Robotics ({ICORR})},
   author = {Pesenti, M. and Gandolla, M. and Pedrocchi, A. and Roveda, L.},
   pages = {1--6},
   year = {2022},
   doi = {10.1109/ICORR55369.2022.9896514},
   url = {}
}
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Pozzi, L., Gandolla, M., Pura, F., Maccarini, M., Pedrocchi, A., Braghin, F., Piga, D., Roveda, L. (2022). Grasping learning, optimization, and knowledge transfer in the robotics field. Scientific Reports 12(1), 4481.

Grasping learning, optimization, and knowledge transfer in the robotics field

@ARTICLE{Roveda2022c,
   title = {Grasping learning, optimization, and knowledge transfer in the robotics field},
   journal = {Scientific Reports},
   volume = {12},
   author = {Pozzi, L. and Gandolla, M. and Pura, F. and Maccarini, M. and Pedrocchi, A. and Braghin, F. and Piga, D. and Roveda, L.},
   number = {1},
   pages = {4481},
   year = {2022},
   doi = {10.1038/s41598-022-08276-z},
   url = {}
}
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Pozzi, L., Gandolla, M., Roveda, L. (2022). Pointing Gestures for Human-Robot Interaction in Service Robotics: a feasibility study. In Computers Helping People with Special Needs, Springer International Publishing, pp. 461–468.

Pointing Gestures for Human-Robot Interaction in Service Robotics: a feasibility study

@INPROCEEDINGS{Rovedag,
   title = {Pointing {G}estures for {H}uman-{R}obot {I}nteraction in {S}ervice {R}obotics: a feasibility study},
   publisher = {Springer International Publishing},
   booktitle = {Computers Helping People {w}ith Special Needs},
   author = {Pozzi, L. and Gandolla, M. and Roveda, L.},
   pages = {461--468},
   year = {2022},
   doi = {10.1007/978-3-031-08645-8 54},
   url = {}
}
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Ravasi, D., Mangili, F., Huber, D., Azzimonti, L., Engeler, L., Vermes, N., Del Rio, G., Guidi, V., Tonolla, M., Flacio, E. (2022). Risk-based mapping tools for surveillance and control of the invasive mosquito Aedes albopictus in Switzerland. International Journal of Environmental Research and Public Health 19(6), 3220.

Risk-based mapping tools for surveillance and control of the invasive mosquito Aedes albopictus in Switzerland

@ARTICLE{mangili2022b,
   title = {Risk-based mapping tools for surveillance and control of the invasive mosquito {A}edes albopictus in {S}witzerland},
   journal = {International Journal of Environmental Research and Public Health},
   volume = {19},
   author = {Ravasi, D. and Mangili, F. and Huber, D. and Azzimonti, L. and Engeler, L. and Vermes, N. and Del Rio, G. and Guidi, V. and Tonolla, M. and Flacio, E.},
   number = {6},
   pages = {3220},
   year = {2022},
   doi = {10.3390/ijerph19063220},
   url = {}
}
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Ravasi, D., Mangili, F., Huber, D., Cannata, M., Strigaro, D., Flacio, E. (2022). The effects of microclimatic winter conditions in urban areas on the risk of establishment for Aedes albopictus. Scientific Reports 12(1), pp. 1–14.

The effects of microclimatic winter conditions in urban areas on the risk of establishment for Aedes albopictus

@ARTICLE{mangili2022c,
   title = {The effects of microclimatic winter conditions in urban areas on the risk of establishment for {A}edes albopictus},
   journal = {Scientific Reports},
   publisher = {Nature Publishing Group},
   volume = {12},
   author = {Ravasi, D. and Mangili, F. and Huber, D. and Cannata, M. and Strigaro, D. and Flacio, E.},
   number = {1},
   pages = {1--14},
   year = {2022},
   doi = {10.1038/s41598-022-20436-9},
   url = {}
}
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Rinaldi, A., Lazareth, H., Poindessous, V., Nemazanyy, I., Sampaio, J.L., Malpetti, D., Bignon, Y., Naesens, M., Rabant, M., Anglicheau, D., Cippà, P.E., Pallet, N. (2022). Impaired fatty acid metabolism perpetuates lipotoxicity along the transition to chronic kidney injury. JCI Insight 7(18).

Impaired fatty acid metabolism perpetuates lipotoxicity along the transition to chronic kidney injury

@ARTICLE{malpetti2022a,
   title = {Impaired fatty acid metabolism perpetuates lipotoxicity along the transition to chronic kidney injury},
   journal = {{JCI} Insight},
   editor = {The American Society for Clinical Investigation},
   volume = {7},
   author = {Rinaldi, A. and Lazareth, H. and Poindessous, V. and Nemazanyy, I. and Sampaio, J.L. and Malpetti, D. and Bignon, Y. and Naesens, M. and Rabant, M. and Anglicheau, D. and Cipp\`a, P.E. and Pallet, N.},
   number = {18},
   year = {2022},
   doi = {10.1172/jci.insight.161783},
   url = {}
}
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Roveda, L., Bussolan, A., Braghin, F., Piga, D. (2022). Robot joint friction compensation learning enhanced by 6D virtual sensor. International Journal of Robust and Nonlinear Control 32(9), pp. 5741–5763.

Robot joint friction compensation learning enhanced by 6D virtual sensor

@ARTICLE{Roveda2022d,
   title = {Robot joint friction compensation learning enhanced by {6D} virtual sensor},
   journal = {International Journal of Robust and Nonlinear Control},
   volume = {32},
   author = {Roveda, L. and Bussolan, A. and Braghin, F. and Piga, D.},
   number = {9},
   pages = {5741--5763},
   year = {2022},
   doi = {10.1002/rnc.6108},
   url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/rnc.6108}
}
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Roveda, L., Maroni, M., Mazzuchelli, L., Praolini, L., Shahid, A.A., Bucca, G., Piga, D. (2022). Robot end-effector mounted camera pose optimization in object detection-based tasks. Journal of Intelligent & Robotic Systems 104(1), 16.

Robot end-effector mounted camera pose optimization in object detection-based tasks

@ARTICLE{Roveda2022e,
   title = {Robot end-effector mounted camera pose optimization in object detection-based tasks},
   journal = {Journal of Intelligent & Robotic Systems},
   volume = {104},
   author = {Roveda, L. and Maroni, M. and Mazzuchelli, L. and Praolini, L. and Shahid, A.A. and Bucca, G. and Piga, D.},
   number = {1},
   pages = {16},
   year = {2022},
   doi = {10.1007/s10846-021-01558-0},
   url = {}
}
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Roveda, L., Pesenti, M., Rossi, M., Covarrubias, M., Galluzzi, C., Combi, S., Pedrocchi, A., Braghin, F., Gandolla, M. (2022). User-centered back-support exoskeleton: design and prototyping. Procedia CIRP 107, pp. 522–527.

User-centered back-support exoskeleton: design and prototyping

@ARTICLE{Roveda2022i,
   title = {User-centered back-support exoskeleton: design and prototyping},
   journal = {Procedia {CIRP}},
   volume = {107},
   author = {Roveda, L. and Pesenti, M. and Rossi, M. and Covarrubias, M. and Galluzzi, C. and Combi, S. and Pedrocchi, A. and Braghin, F. and Gandolla, M.},
   pages = {522--527},
   year = {2022},
   doi = {10.1016/j.procir.2022.05.019},
   url = {}
}
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Roveda, L., Testa, A., Shahid, A.A., Braghin, F., Piga, D. (2022). Q-learning-based model predictive variable impedance control for physical human-robot collaboration. Artificial Intelligence, 103771.

Q-learning-based model predictive variable impedance control for physical human-robot collaboration

@ARTICLE{Roveda2022a,
   title = {Q-learning-based model predictive variable impedance control for physical human-robot collaboration},
   journal = {Artificial Intelligence},
   author = {Roveda, L. and Testa, A. and Shahid, A.A. and Braghin, F. and Piga, D.},
   pages = {103771},
   year = {2022},
   doi = {10.1016/j.artint.2022.103771},
   url = {}
}
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Scutari, M. (2022). Comments on: Hybrid Semiparametric Bayesian Networks. TEST 31, pp. 328–330.

Comments on: Hybrid Semiparametric Bayesian Networks

@ARTICLE{scutari22d,
   title = {Comments on: {H}ybrid {S}emiparametric {B}ayesian {N}etworks},
   journal = {{TEST}},
   volume = {31},
   author = {Scutari, M.},
   pages = {328--330},
   year = {2022},
   doi = {10.1007/s11749-022-00818-x},
   url = {}
}
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Scutari, M., Marquis, C., Azzimonti, L. (2022). Using mixed-effects models to learn bayesian networks from related data sets. In Salmerón, A., Rumı́, R. (Eds), Proceedings of The 11th International Conference on Probabilistic Graphical Models, PMLR 186, JMLR.org, pp. 73–84.

Using mixed-effects models to learn bayesian networks from related data sets

@INPROCEEDINGS{scutari2022a,
   title = {Using mixed-effects models to learn bayesian networks from related data sets},
   editor = {Salmer\'on, A. and Rumı́, R.},
   publisher = {JMLR.org},
   series = {PMLR},
   volume = {186},
   booktitle = {Proceedings of The 11th International Conference on Probabilistic Graphical Models},
   author = {Scutari, M. and Marquis, C. and Azzimonti, L.},
   pages = {73--84},
   year = {2022},
   doi = {},
   url = {https://proceedings.mlr.press/v186/scutari22a.html}
}
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Scutari, M., Panero, F., Proissl, M. (2022). Achieving fairness with a simple ridge penalty. Statistics and Computing 32(5), 77.

Achieving fairness with a simple ridge penalty

@ARTICLE{scutari22a,
   title = {Achieving fairness with a simple ridge penalty},
   journal = {Statistics and Computing},
   volume = {32},
   author = {Scutari, M. and Panero, F. and Proissl, M.},
   number = {5},
   pages = {77},
   year = {2022},
   doi = {10.1007/s11222-022-10143-w},
   url = {}
}
Download
Shahid, A.A., Piga, D., Braghin, F., Roveda, L. (2022). Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning. Autonomous Robots 46(3), pp. 483–498.

Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning

@ARTICLE{Roveda2022b,
   title = {Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning},
   journal = {Autonomous Robots},
   volume = {46},
   author = {Shahid, A.A. and Piga, D. and Braghin, F. and Roveda, L.},
   number = {3},
   pages = {483--498},
   year = {2022},
   doi = {10.1007/s10514-022-10034-z},
   url = {}
}
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Slavakis, K., Shetty, G.N., Cannelli, L., Scutari, G., Nakarmi, U., Ying, L. (2022). Kernel regression imputation in manifolds via bi-linear modeling: the dynamic-MRI case. IEEE Transactions on Computational Imaging 8, pp. 133–147.

Kernel regression imputation in manifolds via bi-linear modeling: the dynamic-MRI case

@ARTICLE{cannelli2022a,
   title = {Kernel regression imputation in manifolds via bi-linear modeling: the dynamic-{MRI} case},
   journal = {{IEEE} Transactions on Computational Imaging},
   volume = {8},
   author = {Slavakis, K. and Shetty, G.N. and Cannelli, L. and Scutari, G. and Nakarmi, U. and Ying, L.},
   pages = {133--147},
   year = {2022},
   doi = {10.1109/TCI.2022.3148062},
   url = {}
}
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Szehr, O., Zarouf, R. (2022). On the asymptotic behavior of Jacobi polynomials with first varying parameter. Journal of Approximation Theory (277), 105702.

On the asymptotic behavior of Jacobi polynomials with first varying parameter

@ARTICLE{szehr2022a,
   title = {On the asymptotic behavior of {J}acobi polynomials with first varying parameter},
   journal = {Journal of Approximation Theory},
   author = {Szehr, O. and Zarouf, R.},
   number = {277},
   pages = {105702},
   year = {2022},
   doi = {10.1016/j.jat.2022.105702},
   url = {}
}
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Zaffalon, M., Antonucci, A., Cabañas, R., Huber, D., Azzimonti, D. (2022). Bounding counterfactuals under selection bias. In Salmerón, A., Rumí, R. (Eds), Proceedings of PGM 2022, PMLR 186, JMLR.org, pp. 289–300.

Bounding counterfactuals under selection bias

@INPROCEEDINGS{zaffalon2022a,
   title = {Bounding counterfactuals under selection bias},
   editor = {Salmerón, A. and Rumí, R.},
   publisher = {JMLR.org},
   series = {PMLR},
   volume = {186},
   booktitle = {Proceedings of {PGM} 2022},
   author = {Zaffalon, M. and Antonucci, A. and Cabañas, R. and Huber, D. and Azzimonti, D.},
   pages = {289--300},
   year = {2022},
   doi = {},
   url = {https://proceedings.mlr.press/v186/zaffalon22a.html}
}
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top

2021

Antonucci, A., Facchini, A., Mattei, L. (2021). Structural learning of probabilistic sentential decision diagrams under partial closed-world assumption. In 4th Workshop on Tractable Probabilistic Modeling (TPM 2021 co-located with UAI 2021).

Structural learning of probabilistic sentential decision diagrams under partial closed-world assumption

@INPROCEEDINGS{antonucci2021e,
   title = {Structural learning of probabilistic sentential decision diagrams under partial closed-world assumption},
   booktitle = {4th Workshop on Tractable Probabilistic Modeling ({TPM} 2021 {c}o-{l}ocated {w}ith {UAI} 2021)},
   author = {Antonucci, A. and Facchini, A. and Mattei, L.},
   year = {2021},
   doi = {10.48550/arXiv.2107.12130},
   url = {}
}
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Antonucci, A., Mangili, F., Bonesana, C., Adorni, G. (2021). A new score for adaptive tests in Bayesian and credal networks. In Vejnarová, J., Wilson, N. (Eds), Symbolic and Quantitative Approaches to Reasoning With Uncertainty, Springer International Publishing, Cham, pp. 399–412.

A new score for adaptive tests in Bayesian and credal networks

@INPROCEEDINGS{antonucci2021c,
   title = {A new score for adaptive tests in {B}ayesian and credal networks},
   editor = {Vejnarov\'a, J. and Wilson, N.},
   publisher = {Springer International Publishing},
   address = {Cham},
   booktitle = {Symbolic and Quantitative Approaches to Reasoning With Uncertainty},
   author = {Antonucci, A. and Mangili, F. and Bonesana, C. and Adorni, G.},
   pages = {399--412},
   year = {2021},
   doi = {10.1007/978-3-030-86772-0_29},
   url = {}
}
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Azzimonti, D., Rottondi, C., Giusti, A., Tornatore, M., Bianco, A. (2021). Comparison of domain adaptation and active learning techniques for quality of transmission estimation with small-sized training datasets [invited]. IEEE/OSA Journal of Optical Communications and Networking 13(1), pp. A56–A66.

Comparison of domain adaptation and active learning techniques for quality of transmission estimation with small-sized training datasets [invited]

@ARTICLE{azzimontid2021,
   title = {Comparison of domain adaptation and active learning techniques for quality of transmission estimation with small-sized training datasets [invited]},
   journal = {{IEEE/OSA} Journal of Optical Communications and Networking},
   volume = {13},
   author = {Azzimonti, D. and Rottondi, C. and Giusti, A. and Tornatore, M. and Bianco, A.},
   number = {1},
   pages = {A56--A66},
   year = {2021},
   doi = {10.1364/JOCN.401918},
   url = {}
}
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Bemporad, A., Piga, D. (2021). Global optimization based on active preference learning with radial basis functions. Machine Learning 110, pp. 417–448.

Global optimization based on active preference learning with radial basis functions

@ARTICLE{piga2021a,
   title = {Global optimization based on active preference learning with radial basis functions},
   journal = {Machine Learning},
   publisher = {Springer},
   volume = {110},
   author = {Bemporad, A. and Piga, D.},
   pages = {417--448},
   year = {2021},
   doi = {10.1007/s10994-020-05935-y},
   url = {}
}
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Benavoli, A., Azzimonti, D., Piga, D. (2021). Preferential bayesian optimisation with skew gaussian processes. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO '21, Association for Computing Machinery, New York, NY, USA, pp. 1842–1850.

Preferential bayesian optimisation with skew gaussian processes

@INPROCEEDINGS{azzimontid2021b,
   title = {Preferential bayesian optimisation with skew gaussian processes},
   publisher = {Association for Computing Machinery},
   address = {New York, NY, USA},
   series = {GECCO '21},
   booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference Companion},
   author = {Benavoli, A. and Azzimonti, D. and Piga, D.},
   pages = {1842--1850},
   year = {2021},
   doi = {10.1145/3449726.3463128},
   url = {}
}
Download
Benavoli, A., Azzimonti, D., Piga, D. (2021). A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with skew gaussian processes. Machine Learning 110(11), pp. 3095–3133.

A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with skew gaussian processes

@ARTICLE{azzimontid2021c,
   title = {A unified framework for closed-form nonparametric regression, classification, preference and mixed problems with skew gaussian processes},
   journal = {Machine Learning},
   volume = {110},
   author = {Benavoli, A. and Azzimonti, D. and Piga, D.},
   number = {11},
   pages = {3095--3133},
   year = {2021},
   doi = {10.1007/s10994-021-06039-x},
   url = {}
}
Download
Benavoli, A., Corani, G. (2021). State Space approximation of Gaussian Processes for time-series forecasting. In Advanced Analytics and Learning on Temporal Data, Springer International Publishing, pp. 21–35.

State Space approximation of Gaussian Processes for time-series forecasting

@INPROCEEDINGS{corani2021b,
   title = {State {S}pace approximation of {G}aussian {P}rocesses for time-series forecasting},
   journal = {Proc. Workshop on Advanced Analytics and Learning on Temporal Data, 6th {ECML} {PKDD} Workshop, {AALTD} 2021},
   publisher = {Springer International Publishing},
   booktitle = {Advanced Analytics and Learning on Temporal Data},
   author = {Benavoli, A. and Corani, G.},
   pages = {21--35},
   year = {2021},
   doi = {10.1007/978-3-030-91445-5_2},
   url = {}
}
Download
Benavoli, A., Facchini, A., Zaffalon, M. (2021). The weirdness theorem and the origin of quantum paradoxes. Foundations of Physics 51(5), 95.

The weirdness theorem and the origin of quantum paradoxes

@ARTICLE{benavoli2021b,
   title = {The weirdness theorem and the origin of quantum paradoxes},
   journal = {Foundations of Physics},
   volume = {51},
   author = {Benavoli, A., Facchini, A., Zaffalon, M.},
   number = {5},
   pages = {95},
   year = {2021},
   doi = {10.1007/s10701-021-00499-w},
   url = {}
}
Download
Benavoli, A., Facchini, A., Zaffalon, M. (2021). Quantum indistinguishability through exchangeable desirable gambles. In De Bock, J., Cano, A., Miranda, E., Moral, S. (Ed), ISIPTA 2021, PMLR 147, JMLR.org, pp. 22–31.

Quantum indistinguishability through exchangeable desirable gambles

@INPROCEEDINGS{benavoli2021a,
   title = {Quantum indistinguishability through exchangeable desirable gambles},
   editor = {De Bock, J., Cano, A., Miranda, E., Moral, S.},
   publisher = {JMLR.org},
   series = {PMLR},
   volume = {147},
   booktitle = {{ISIPTA} 2021},
   author = {Benavoli, A., Facchini, A., Zaffalon, M.},
   pages = {22--31},
   year = {2021},
   doi = {},
   url = {https://isipta21.sipta.org/papers.html}
}
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Berjano, P., Langella, F., Ventriglia, L., Compagnone, D., Barletta, P., Huber, D., Mangili, F., Licandro, G., Galbusera, F., Cina, A., Bassani, T., Lamartina, C., Scaramuzzo, L., Bassani, R., Brayda-Bruno, M., Villafañe, J.H., Monti, L., Azzimonti, L. (2021). The influence of baseline clinical status and surgical strategy on early good to excellent result in spinal lumbar arthrodesis: a machine learning approach. Journal of Personalized Medicine 11(12), 1377.

The influence of baseline clinical status and surgical strategy on early good to excellent result in spinal lumbar arthrodesis: a machine learning approach

@ARTICLE{azzimonti2021b,
   title = {The influence of baseline clinical status and surgical strategy on early good to excellent result in spinal lumbar arthrodesis: a machine learning approach},
   journal = {Journal of Personalized Medicine},
   volume = {11},
   author = {Berjano, P. and Langella, F. and Ventriglia, L. and Compagnone, D. and Barletta, P. and Huber, D. and Mangili, F. and Licandro, G. and Galbusera, F. and Cina, A. and Bassani, T. and Lamartina, C. and Scaramuzzo, L. and Bassani, R. and Brayda-Bruno, M. and Villafa\~ne, J.H. and Monti, L. and Azzimonti, L.},
   number = {12},
   pages = {1377},
   year = {2021},
   doi = {10.3390/jpm11121377},
   url = {}
}
Download
Bianchi, F., Breschi, V., Piga, D., Piroddi, L. (2021). Model structure selection for switched narx system identification: a randomized approach. Automatica 125, 109415.

Model structure selection for switched narx system identification: a randomized approach

@ARTICLE{piga2021c,
   title = {Model structure selection for switched narx system identification: a randomized approach},
   journal = {Automatica},
   volume = {125},
   author = {Bianchi, F. and Breschi, V. and Piga, D. and Piroddi, L.},
   pages = {109415},
   year = {2021},
   doi = {10.1016/j.automatica.2020.109415},
   url = {}
}
Download
Bini, F., Pica, A., Azzimonti, L., Giusti, A., Ruinelli, L., Marinozzi, F., Trimboli, P. (2021). Artificial intelligence in thyroid field. A comprehensive review. Cancers 13(19), 4740.

Artificial intelligence in thyroid field. A comprehensive review

@ARTICLE{azzimonti2021a,
   title = {Artificial intelligence in thyroid field. A comprehensive review},
   journal = {Cancers},
   volume = {13},
   author = {Bini, F. and Pica, A. and Azzimonti, L. and Giusti, A. and Ruinelli, L. and Marinozzi, F. and Trimboli, P.},
   number = {19},
   pages = {4740},
   year = {2021},
   doi = {10.3390/cancers13194740},
   url = {https://www.mdpi.com/2072-6694/13/19/4740}
}
Download
Bodewes, T., Scutari, M. (2021). Learning bayesian networks from incomplete data with the node-averaged likelihood. International Journal of Approximate Reasoning 138, pp. 145–160.

Learning bayesian networks from incomplete data with the node-averaged likelihood

@ARTICLE{scutari21d,
   title = {Learning bayesian networks from incomplete data with the node-averaged likelihood},
   journal = {International Journal of Approximate Reasoning},
   volume = {138},
   author = {Bodewes, T. and Scutari, M.},
   pages = {145--160},
   year = {2021},
   doi = {10.1016/j.ijar.2021.07.015},
   url = {}
}
Download
Bonesana, C., Mangili, F., Antonucci, A. (2021). ADAPQUEST: a software for web-based adaptive questionnaires based on Bayesian networks. In AI4EDU: Artificial Intelligence for Education (@ Ijcai2021), Virtual Event.

ADAPQUEST: a software for web-based adaptive questionnaires based on Bayesian networks

@INPROCEEDINGS{bonesana2021a,
   title = {{ADAPQUEST}: a software for web-based adaptive questionnaires based on {B}ayesian networks},
   address = {Virtual Event},
   booktitle = {{AI4EDU}: Artificial Intelligence for Education (@ Ijcai2021)},
   author = {Bonesana, C. and Mangili, F. and Antonucci, A.},
   year = {2021},
   doi = {10.48550/arXiv.2112.14476},
   url = {}
}
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Bregoli, A., Scutari, M., Stella, F. (2021). A constraint-based algorithm for the structural learning of continuous-time bayesian networks. International Journal of Approximate Reasoning 138, pp. 105–122.

A constraint-based algorithm for the structural learning of continuous-time bayesian networks

@ARTICLE{scutari21e,
   title = {A constraint-based algorithm for the structural learning of continuous-time bayesian networks},
   journal = {International Journal of Approximate Reasoning},
   volume = {138},
   author = {Bregoli, A. and Scutari, M. and Stella, F.},
   pages = {105--122},
   year = {2021},
   doi = {10.1016/j.ijar.2021.08.005},
   url = {}
}
Download
Cabañas, R., Antonucci, A. (2021). CREPO: an open repository to benchmark credal network algorithms. In De Bock, J., Cano, A., Miranda, E., Moral, S. (Eds), International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA-2021) 147, JMLR.org.

CREPO: an open repository to benchmark credal network algorithms

@INPROCEEDINGS{cabanas2021b,
   title = {{CREPO}: an open repository to benchmark credal network algorithms},
   editor = {De Bock, J. and Cano, A. and Miranda, E. and Moral, S.},
   publisher = {JMLR.org},
   volume = {147},
   booktitle = {International Symposium on Imprecise Probabilities: Theories and Applications ({ISIPTA}-2021)},
   author = {Caba\~nas, R. and Antonucci, A.},
   year = {2021},
   doi = {},
   url = {http://proceedings.mlr.press/v147/cabanas21a/cabanas21a.pdf}
}
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Casanova, A., Benavoli, A., Zaffalon, M. (2021). Nonlinear desirability as a linear classification problem. In Proceedings of Machine Learning Research 147, pp. 617–71.

Nonlinear desirability as a linear classification problem

@INPROCEEDINGS{casanova2021c,
   title = {Nonlinear desirability as a linear classification problem},
   volume = {147},
   booktitle = {Proceedings of Machine Learning Research},
   author = {Casanova, A. and Benavoli, A. and Zaffalon, M.},
   pages = {617--71},
   year = {2021},
   doi = {},
   url = {https://proceedings.mlr.press/v147/casanova21a.html}
}
Download
Casanova, A., Kohlas, J., Zaffalon, M. (2021). Algebras of sets and coherent sets of gambles. In Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Springer International Publishing, pp. 603–615.

Algebras of sets and coherent sets of gambles

@INPROCEEDINGS{casanova2021d,
   title = {Algebras of sets and coherent sets of gambles},
   publisher = {Springer International Publishing},
   booktitle = {Symbolic and Quantitative Approaches to Reasoning {w}ith Uncertainty},
   author = {Casanova, A. and Kohlas, J. and Zaffalon, M.},
   pages = {603--615},
   year = {2021},
   doi = {10.1007/978-3-030-86772-0_43},
   url = {}
}
Download
Casanova, A., Miranda, E., Zaffalon, M. (2021). Joint desirability foundations of social choice and opinion pooling. Annals of Mathematics and Artificial Intelligence 89(10–11), pp. 965–1011.

Joint desirability foundations of social choice and opinion pooling

@ARTICLE{casanova2021a,
   title = {Joint desirability foundations of social choice and opinion pooling},
   journal = {Annals of Mathematics and Artificial Intelligence},
   volume = {89},
   author = {Casanova, A. and Miranda, E. and Zaffalon, M.},
   number = {10--11},
   pages = {965--1011},
   year = {2021},
   doi = {10.1007/s10472-021-09733-7},
   url = {}
}
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Corani, G., Benavoli, A., Zaffalon, M. (2021). Time series forecasting with Gaussian Processes needs priors. In European Conference on Machine Learning and Knowledge Discovery in Databases, pp. 103–117.

Time series forecasting with Gaussian Processes needs priors

@INPROCEEDINGS{corani2021a,
   title = {Time series forecasting with {G}aussian {P}rocesses needs priors},
   booktitle = {European Conference on Machine Learning and Knowledge Discovery in Databases},
   author = {Corani, G. and Benavoli, A. and Zaffalon, M.},
   pages = {103--117},
   year = {2021},
   doi = {10.1007/978-3-030-86514-6_7},
   url = {}
}
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Forgione, M., Piga, D. (2021). dynoNet: a neural network architecture for learning dynamical systems. International Journal of Adaptive Control and Signal Processing 35, pp. 612–626.

dynoNet: a neural network architecture for learning dynamical systems

@ARTICLE{forgione2021a,
   title = {{dynoNet}: a neural network architecture for learning dynamical systems},
   journal = {International Journal of Adaptive Control and Signal Processing},
   volume = {35},
   author = {Forgione, M. and Piga, D.},
   pages = {612--626},
   year = {2021},
   doi = {10.1002/acs.3216},
   url = {}
}
Download
Forgione, M., Piga, D. (2021). Continuous-time system identification with neural networks: model structures and fitting criteria. European Journal of Control 59, pp. 69–81.

Continuous-time system identification with neural networks: model structures and fitting criteria

@ARTICLE{forgione2021b,
   title = {Continuous-time system identification with neural networks: model structures and fitting criteria},
   journal = {European Journal of Control},
   volume = {59},
   author = {Forgione, M. and Piga, D.},
   pages = {69--81},
   year = {2021},
   doi = {10.1016/j.ejcon.2021.01.008},
   url = {}
}
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Dalla Gasperina, S., Roveda, L., Pedrocchi, A., Braghin, F., Gandolla, M. (2021). Review on patient-cooperative control strategies for upper-limb rehabilitation exoskeletons. Frontiers in Robotics and AI 8.

Review on patient-cooperative control strategies for upper-limb rehabilitation exoskeletons

@ARTICLE{Roveda2021e,
   title = {Review on patient-cooperative control strategies for upper-limb rehabilitation exoskeletons},
   journal = {Frontiers in Robotics and {AI}},
   volume = {8},
   author = {Dalla Gasperina, S. and Roveda, L. and Pedrocchi, A. and Braghin, F. and Gandolla, M.},
   year = {2021},
   doi = {10.3389/frobt.2021.745018},
   url = {}
}
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Geluykens, J., Mitrovic, S., Vázquez, C.O., Laino, T., Vaucher, A.C., Weerdt, J.D. (2021). Neural machine translation for conditional generation of novel procedures. In 54th Hawaii International Conference on System Sciences, HICSS 2021, Kauai, Hawaii, Usa, January 5, 2021, ScholarSpace, pp. 1–10.

Neural machine translation for conditional generation of novel procedures

@INPROCEEDINGS{mitrovic2021b,
   title = {Neural machine translation for conditional generation of novel procedures},
   publisher = {ScholarSpace},
   booktitle = {54th Hawaii International Conference on System Sciences, {HICSS} 2021, Kauai, Hawaii, Usa, January 5, 2021},
   author = {Geluykens, J. and Mitrovic, S. and V\'azquez, C.O. and Laino, T. and Vaucher, A.C. and Weerdt, J.D.},
   pages = {1--10},
   year = {2021},
   doi = {},
   url = {http://hdl.handle.net/10125/70744}
}
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Gómez-Olmedo, M., Cabañas, R., Cano, A., Moral, S., Retamero, O.P. (2021). Value-based potentials: exploiting quantitative information regularity patterns in probabilistic graphical models. International Journal of Intelligent Systems 36(11), pp. 6913–6943.

Value-based potentials: exploiting quantitative information regularity patterns in probabilistic graphical models

@ARTICLE{cabanas2021c,
   title = {Value-based potentials: exploiting quantitative information regularity patterns in probabilistic graphical models},
   journal = {International Journal of Intelligent Systems},
   volume = {36},
   author = {G\'omez-Olmedo, M. and Caba\~nas, R. and Cano, A. and Moral, S. and Retamero, O.P.},
   number = {11},
   pages = {6913--6943},
   year = {2021},
   doi = {10.1002/int.22573},
   url = {}
}
Download
Grasso, G., Gregorio, A.D., Mavkov, B., Piga, D., Labate, G.F.D., Danani, A., Deriu, M.A. (2021). Fragmented blind docking: a novel protein–ligand binding prediction protocol. Journal of Biomolecular Structure and Dynamics 40(24), pp. 13472–13481.

Fragmented blind docking: a novel protein–ligand binding prediction protocol

@ARTICLE{piga2021f,
   title = {Fragmented blind docking: a novel protein--ligand binding prediction protocol},
   journal = {Journal of Biomolecular Structure and Dynamics},
   publisher = {Taylor & Francis},
   volume = {40},
   author = {Grasso, G. and Gregorio, A.D. and Mavkov, B. and Piga, D. and Labate, G.F.D. and Danani, A. and Deriu, M.A.},
   number = {24},
   pages = {13472--13481},
   year = {2021},
   doi = {10.1080/07391102.2021.1988709},
   url = {}
}
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Halasz, G., Sperti, M., Villani, M., Michelucci, U., Agostoni, P., Biagi, A., Rossi, L., Botti, A., Mari, C., Maccarini, M., Pura, F., Roveda, L., Nardecchia, A., Mottola, E., Nolli, M., Salvioni, E., Mapelli, M., Deriu, M.A., Piga, D., Piepoli, M. (2021). A machine learning approach for mortality prediction in covid-19 pneumonia: development and evaluation of the piacenza score. Journal of Medical Internet Research 23(5), e29058.

A machine learning approach for mortality prediction in covid-19 pneumonia: development and evaluation of the piacenza score

@ARTICLE{piga2021g,
   title = {A machine learning approach for mortality prediction in covid-19 pneumonia: development and evaluation of the piacenza score},
   journal = {Journal of Medical Internet Research},
   volume = {23},
   author = {Halasz, G. and Sperti, M. and Villani, M. and Michelucci, U. and Agostoni, P. and Biagi, A. and Rossi, L. and Botti, A. and Mari, C. and Maccarini, M. and Pura, F. and Roveda, L. and Nardecchia, A. and Mottola, E. and Nolli, M. and Salvioni, E. and Mapelli, M. and Deriu, M.A. and Piga, D. and Piepoli, M.},
   number = {5},
   pages = {e29058},
   year = {2021},
   doi = {10.2196/29058},
   url = {}
}
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Kania, L., Schürch, M., Azzimonti, D., Benavoli, A. (2021). Sparse information filter for fast gaussian process regression. In Oliver, N., Pérez-Cruz, F., Kramer, S., Read, J., Lozano, J.A. (Eds), Machine Learning and Knowledge Discovery in Databases. Research Track, Springer International Publishing, Cham, pp. 527–542.

Sparse information filter for fast gaussian process regression

@INPROCEEDINGS{schurch2021a,
   title = {Sparse information filter for fast gaussian process regression},
   editor = {Oliver, N. and P\'erez-Cruz, F. and Kramer, S. and Read, J. and Lozano, J.A.},
   publisher = {Springer International Publishing},
   address = {Cham},
   booktitle = {Machine Learning and Knowledge Discovery in Databases. Research Track},
   author = {Kania, L. and Sch\"urch, M. and Azzimonti, D. and Benavoli, A.},
   pages = {527--542},
   year = {2021},
   doi = {10.1007/978-3-030-86523-8_32},
   url = {}
}
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Kanjirangat, V., Rinaldi, F. (2021). Enhancing Biomedical Relation Extraction with Transformer Models using Shortest Dependency Path Features and Triplet Information. Journal of Biomedical Informatics, 103893.

Enhancing Biomedical Relation Extraction with Transformer Models using Shortest Dependency Path Features and Triplet Information

@ARTICLE{vani2021b,
   title = {Enhancing {B}iomedical {R}elation {E}xtraction with {T}ransformer {M}odels using {S}hortest {D}ependency {P}ath {F}eatures and {T}riplet {I}nformation},
   journal = {Journal of Biomedical Informatics},
   publisher = {Elsevier},
   author = {Kanjirangat, V. and Rinaldi, F.},
   pages = {103893},
   year = {2021},
   doi = {10.1016/j.jbi.2021.103893},
   url = {}
}
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Kohlas, J., Casanova, A., Zaffalon, M. (2021). Information algebras of coherent sets of gambles in general possibility spaces. In Proceedings of Machine Learning Research 147, pp. 191–200.

Information algebras of coherent sets of gambles in general possibility spaces

@INPROCEEDINGS{casanova2021b,
   title = {Information algebras of coherent sets of gambles in general possibility spaces},
   volume = {147},
   booktitle = {Proceedings of Machine Learning Research},
   author = {Kohlas, J. and Casanova, A. and Zaffalon, M.},
   pages = {191--200},
   year = {2021},
   doi = {},
   url = {http://proceedings.mlr.press/v147/kohlas21a/kohlas21a.pdf}
}
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Liew, B.X.W., Ford, J.J., Scutari, M., Hahne, A.J. (2021). How does individualised physiotherapy work for people with low back pain? A Bayesian Network analysis using randomised controlled trial data. PLoS ONE 16, pp. 1–16.

How does individualised physiotherapy work for people with low back pain? A Bayesian Network analysis using randomised controlled trial data

@ARTICLE{scutari21c,
   title = {How does individualised physiotherapy work for people with low back pain? A {B}ayesian {N}etwork analysis using randomised controlled trial data},
   journal = {{PLoS} {ONE}},
   volume = {16},
   author = {Liew, B.X.W. and Ford, J.J. and Scutari, M. and Hahne, A.J.},
   pages = {1--16},
   year = {2021},
   doi = {10.1371/journal.pone.0258515},
   url = {}
}
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Liew, B.X.W., Peolsson, A., Falla, D., Cleland, J.A., Scutari, M., Kierkegaard, M., r A Dedering, (2021). Mechanisms of recovery after neck-specific or general exercises in patients with cervical radiculopathy. European Journal of Pain 25(5), pp. 1162–1172.

Mechanisms of recovery after neck-specific or general exercises in patients with cervical radiculopathy

@ARTICLE{scutari21b,
   title = {Mechanisms of recovery after neck-specific or general exercises in patients with cervical radiculopathy},
   journal = {European Journal of Pain},
   volume = {25},
   author = {Liew, B.X.W. and Peolsson, A. and Falla, D. and Cleland, J.A. and Scutari, M. and Kierkegaard, M. and r A Dedering, },
   number = {5},
   pages = {1162--1172},
   year = {2021},
   doi = {10.1002/ejp.1741},
   url = {}
}
Download
Llerena, J.V., Mauá, D.D., Antonucci, A. (2021). Cautious classification with data missing not at random using generative random forests. In Vejnarová, J., Wilson, N. (Eds), Symbolic and Quantitative Approaches to Reasoning With Uncertainty, Springer International Publishing, Cham, pp. 284–298.

Cautious classification with data missing not at random using generative random forests

@INPROCEEDINGS{antonucci2021b,
   title = {Cautious classification with data missing not at random using generative random forests},
   editor = {Vejnarov\'a, J. and Wilson, N.},
   publisher = {Springer International Publishing},
   address = {Cham},
   booktitle = {Symbolic and Quantitative Approaches to Reasoning With Uncertainty},
   author = {Llerena, J.V. and Mau\'a, D.D. and Antonucci, A.},
   pages = {284--298},
   year = {2021},
   doi = {10.1007/978-3-030-86772-0_21},
   url = {}
}
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Maggioni, B., Marescotti, E., Zanchettin, M., Piga, D., Roveda, L. (2021). Velocity planning of a robotic task enhanced by fuzzy logic and dynamic movement primitives. In .

Velocity planning of a robotic task enhanced by fuzzy logic and dynamic movement primitives

@INPROCEEDINGS{Roveda2021g,
   title = {Velocity planning of a robotic task enhanced by fuzzy logic and dynamic movement primitives},
   journal = {{ARCI} 2021},
   author = {Maggioni, B. and Marescotti, E. and Zanchettin, M. and Piga, D. and Roveda, L.},
   year = {2021},
   doi = {},
   url = {}
}
Download
Pedrero-Martin, Y., Falla, D., Martinez-Calderon, J., Liew, B.X.W., Scutari, M., Luque-Suarez, A. (2021). Self-efficacy beliefs mediate the association between pain intensity and pain interference in acute/subacute whiplash-associated disorders. European Spine Journal 20(6), pp. 1689–1698.

Self-efficacy beliefs mediate the association between pain intensity and pain interference in acute/subacute whiplash-associated disorders

@ARTICLE{scutari21a,
   title = {Self-efficacy beliefs mediate the association between pain intensity and pain interference in acute/subacute whiplash-associated disorders},
   journal = {European Spine Journal},
   volume = {20},
   author = {Pedrero-Martin, Y. and Falla, D. and Martinez-Calderon, J. and Liew, B.X.W. and Scutari, M. and Luque-Suarez, A.},
   number = {6},
   pages = {1689--1698},
   year = {2021},
   doi = {10.1007/s00586-021-06731-5},
   url = {}
}
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Masegosa, A.R., Cabañas, R., Langseth, H., Nielsen, T.D., Salmerón, A. (2021). Probabilistic models with deep neural networks. Entropy 23(1), 117.

Probabilistic models with deep neural networks

@ARTICLE{cabanas2021a,
   title = {Probabilistic models with deep neural networks},
   journal = {Entropy},
   volume = {23},
   author = {Masegosa, A.R. and Caba\~nas, R. and Langseth, H. and Nielsen, T.D. and Salmer\'on, A.},
   number = {1},
   pages = {117},
   year = {2021},
   doi = {10.3390/e23010117},
   url = {}
}
Download
Mejari, M., Mavkov, B., Forgione, M., Piga, D. (2021). An integral architecture for identification of continuous-time state-space lpv models. In 4th IFAC Workshop on Linear Parameter-Varying Systems LPVS 2021 54(8), Milan, Italy, pp. 7–12.

An integral architecture for identification of continuous-time state-space lpv models

@INPROCEEDINGS{mejari2021a,
   title = {An integral architecture for identification of continuous-time state-space lpv models},
   journal = {{IFAC}-{PapersOnLine}},
   address = {Milan, Italy},
   volume = {54},
   booktitle = {4th {IFAC} Workshop on Linear Parameter-Varying Systems {LPVS} 2021},
   author = {Mejari, M. and Mavkov, B. and Forgione, M. and Piga, D.},
   number = {8},
   pages = {7--12},
   year = {2021},
   doi = {10.1016/j.ifacol.2021.08.573},
   url = {}
}
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Mellace, S., Kanjirangat, V., Antonucci, A. (2021). Relation clustering in narrative knowledge graphs. In AI4Narratives Workshop at 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 20).

Relation clustering in narrative knowledge graphs

@INPROCEEDINGS{vani2021a,
   title = {Relation clustering in narrative knowledge graphs},
   booktitle = {{AI4Narratives} Workshop at 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence ({IJCAI}-{PRICAI} 20)},
   author = {Mellace, S. and Kanjirangat, V. and Antonucci, A.},
   year = {2021},
   doi = {},
   url = {http://ceur-ws.org/Vol-2794/paper5.pdf}
}
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Michelucci, U., Sperti, M., Piga, D., Venturini, F., Deriu, M.A. (2021). A model-agnostic algorithm for bayes error determination in binary classification. Algorithms 14(11), 301.

A model-agnostic algorithm for bayes error determination in binary classification

@ARTICLE{piga2021d,
   title = {A model-agnostic algorithm for bayes error determination in binary classification},
   journal = {Algorithms},
   volume = {14},
   author = {Michelucci, U. and Sperti, M. and Piga, D. and Venturini, F. and Deriu, M.A.},
   number = {11},
   pages = {301},
   year = {2021},
   doi = {10.3390/a14110301},
   url = {}
}
Download
Awal, M.R., Cao, R., Lee, R.K., Mitrovic, S. (2021). Angrybert: joint learning target and emotion for hate speech detection. In Karlapalem, K., Cheng, H., Ramakrishnan, N., Agrawal, R.K., Reddy, P.K., Srivastava, J., Chakraborty, T. (Eds), Advances in Knowledge Discovery and Data Mining - 25th Pacific-asia Conference, PAKDD 2021, Virtual Event, May 11-14, 2021, Proceedings, Part I, Lecture Notes in Computer Science 12712, Springer, pp. 701–713.

Angrybert: joint learning target and emotion for hate speech detection

@INPROCEEDINGS{mitrovic2021a,
   title = {Angrybert: joint learning target and emotion for hate speech detection},
   editor = {Karlapalem, K. and Cheng, H. and Ramakrishnan, N. and Agrawal, R.K. and Reddy, P.K. and Srivastava, J. and Chakraborty, T.},
   publisher = {Springer},
   series = {Lecture Notes in Computer Science},
   volume = {12712},
   booktitle = {Advances in Knowledge Discovery and Data Mining - 25th Pacific-{a}sia Conference, {PAKDD} 2021, Virtual Event, May 11-14, 2021, Proceedings, Part I},
   author = {Awal, M.R. and Cao, R. and Lee, R.K. and Mitrovic, S.},
   pages = {701--713},
   year = {2021},
   doi = {10.1007/978-3-030-75762-5_55},
   url = {}
}
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Piga, D., Forgione, M., Mejari, M. (2021). Deep learning with transfer functions: New applications in system identification. In Proceedings of the 19th IFAC Symposium System Identification: learning models for decision and control 54(7), pp. 415–420.

Deep learning with transfer functions: New applications in system identification

@INPROCEEDINGS{forgione2021c,
   title = {Deep learning with transfer functions: {N}ew applications in system identification},
   journal = {{IFAC}-{PapersOnLine}},
   volume = {54},
   booktitle = {Proceedings of the 19th {IFAC} Symposium System Identification: {l}earning {m}odels for {d}ecision and {c}ontrol},
   author = {Piga, D. and Forgione, M. and Mejari, M.},
   number = {7},
   pages = {415--420},
   year = {2021},
   doi = {10.1016/j.ifacol.2021.08.395},
   url = {}
}
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Ropero, R.F., Flores, M.J., Cabañas, R., Rumí, R. (2021). A comparison bewteen elvira software and amidst toolbox in environmental data: a case study of flooding risk management. In Proceedings of the 15th Uai Conference on Bayesian Modeling Applications Workshop.

A comparison bewteen elvira software and amidst toolbox in environmental data: a case study of flooding risk management

@INPROCEEDINGS{cabanas2021d,
   title = {A comparison bewteen elvira software and amidst toolbox in environmental data: a case study of flooding risk management},
   booktitle = {Proceedings of the 15th Uai Conference on Bayesian Modeling Applications Workshop},
   author = {Ropero, R.F. and Flores, M.J. and Caba\~nas, R. and Rum\'i, R.},
   year = {2021},
   doi = {},
   url = {}
}
Download
Roveda, L., Maggioni, B., Marescotti, E., Shahid, A., Zanchettin, M., Bemporad, A., Piga, D. (2021). Pairwise preferences-based optimization of a path-based velocity planner in robotic sealing tasks. IEEE Robotics and Automation Letters 6(4), pp. 6632–6639.

Pairwise preferences-based optimization of a path-based velocity planner in robotic sealing tasks

@ARTICLE{Roveda2021c,
   title = {Pairwise preferences-based optimization of a path-based velocity planner in robotic sealing tasks},
   journal = {{IEEE} Robotics and Automation Letters},
   volume = {6},
   author = {Roveda, L. and Maggioni, B. and Marescotti, E. and Shahid, A. and Zanchettin, M. and Bemporad, A. and Piga, D.},
   number = {4},
   pages = {6632--6639},
   year = {2021},
   doi = {10.1109/LRA.2021.3094479},
   url = {}
}
Download
Roveda, L., Maroni, M., Mazzuchelli, L., Praolini, L., Bucca, G., Piga, D. (2021). Enhancing object detection performance through sensor pose Definition with bayesian optimization. In , pp. 699–703.

Enhancing object detection performance through sensor pose Definition with bayesian optimization

@INPROCEEDINGS{Roveda2021h,
   title = {Enhancing object detection performance through sensor pose {D}efinition with bayesian optimization},
   journal = {Metrology2021},
   author = {Roveda, L. and Maroni, M. and Mazzuchelli, L. and Praolini, L. and Bucca, G. and Piga, D.},
   pages = {699--703},
   year = {2021},
   doi = {10.1109/METROIND4.0IOT51437.2021.9488517},
   url = {}
}
Download
Roveda, L., Piga, D. (2021). Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks. Autonomous Robots 45(3), pp. 371–388.

Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks

@ARTICLE{Roveda2021a,
   title = {Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks},
   journal = {Autonomous Robots},
   volume = {45},
   author = {Roveda, L. and Piga, D.},
   number = {3},
   pages = {371--388},
   year = {2021},
   doi = {10.1007/s10514-021-09970-z},
   url = {}
}
Download
Roveda, L., Riva, D., Bucca, G., Piga, D. (2021). External joint torques estimation for a position-controlled manipulator employing an extended kalman filter. In , pp. 101–107.

External joint torques estimation for a position-controlled manipulator employing an extended kalman filter

@INPROCEEDINGS{Roveda2021i,
   title = {External joint torques estimation for a position-controlled manipulator employing an extended kalman filter},
   journal = {{UbiquitousRobots2021}},
   author = {Roveda, L. and Riva, D. and Bucca, G. and Piga, D.},
   pages = {101--107},
   year = {2021},
   doi = {10.1109/UR52253.2021.9494674},
   url = {}
}
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Roveda, L., Riva, D., Bucca, G., Piga, D. (2021). Sensorless optimal switching Impact/Force controller. IEEE Access 9, pp. 158167–158184.

Sensorless optimal switching Impact/Force controller

@ARTICLE{Roveda2021f,
   title = {Sensorless optimal switching {Impact/Force} controller},
   journal = {{IEEE} Access},
   volume = {9},
   author = {Roveda, L. and Riva, D. and Bucca, G. and Piga, D.},
   pages = {158167--158184},
   year = {2021},
   doi = {10.1109/ACCESS.2021.3131390},
   url = {}
}
Download
Roveda, L., Shahid, A., Iannacci, N., Piga, D. (2021). Sensorless optimal interaction control exploiting environment stiffness estimation. IEEE Transactions on Control System Technology 30(1), pp. 218–233.

Sensorless optimal interaction control exploiting environment stiffness estimation

@ARTICLE{Roveda2021b,
   title = {Sensorless optimal interaction control exploiting environment stiffness estimation},
   journal = {{IEEE} Transactions on Control System Technology},
   volume = {30},
   author = {Roveda, L. and Shahid, A. and Iannacci, N. and Piga, D.},
   number = {1},
   pages = {218--233},
   year = {2021},
   doi = {10.1109/TCST.2021.3061091},
   url = {}
}
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Selvi, D., Piga, D., Battistelli, G., Bemporad, A. (2021). Optimal direct data-driven control with stability guarantees. European Journal of Control 59, pp. 175–187.

Optimal direct data-driven control with stability guarantees

@ARTICLE{piga2021b,
   title = {Optimal direct data-driven control with stability guarantees},
   journal = {European Journal of Control},
   volume = {59},
   author = {Selvi, D. and Piga, D. and Battistelli, G. and Bemporad, A.},
   pages = {175--187},
   year = {2021},
   doi = {10.1016/j.ejcon.2020.09.005},
   url = {}
}
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Shahid, A., Sesin, J., Pecioski, D., Braghin, F., Piga, D., Roveda, L. (2021). Decentralized multi-agent control of a manipulator in continuous task learning. MDPI Applied Science 11(21), 10227.

Decentralized multi-agent control of a manipulator in continuous task learning

@ARTICLE{Roveda2021d,
   title = {Decentralized multi-agent control of a manipulator in continuous task learning},
   journal = {{MDPI} Applied Science},
   volume = {11},
   author = {Shahid, A. and Sesin, J. and Pecioski, D. and Braghin, F. and Piga, D. and Roveda, L.},
   number = {21},
   pages = {10227},
   year = {2021},
   doi = {10.3390/app112110227},
   url = {}
}
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Sommer, M., Rüegsegger, M., Szehr, O., Del Rio, G. (2021). Deep self-optimizing artificial intelligence for tactical analysis, training and optimization. In , NATO.

Deep self-optimizing artificial intelligence for tactical analysis, training and optimization

@INPROCEEDINGS{szehr2021b,
   title = {Deep self-optimizing artificial intelligence for tactical analysis, training and optimization},
   journal = {{MSG}-Symposium},
   publisher = {NATO},
   author = {Sommer, M. and R\"uegsegger, M. and Szehr, O. and Del Rio, G.},
   year = {2021},
   doi = {},
   url = {}
}
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Szehr, O., Zarouf, R. (2021). Explicit counterexamples to Schäffer's conjecture. Journal de Mathématiques Pures et Appliquées 146, pp. 1–30.

Explicit counterexamples to Schäffer's conjecture

@ARTICLE{szehr2021a,
   title = {Explicit counterexamples to {S}ch\"affer's conjecture},
   journal = {Journal {d}e Math\'ematiques Pures {e}t Appliqu\'ees},
   volume = {146},
   author = {Szehr, O. and Zarouf, R.},
   pages = {1--30},
   year = {2021},
   doi = {10.1016/j.matpur.2020.10.006},
   url = {}
}
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Termine, A., Antonucci, A., Primiero, G., Facchini, A. (2021). Logic and model checking by imprecise probabilistic interpreted systems. In Rosenfeld, A., Talmon, N. (Eds), Multi-Agent Systems. EUMAS 2021. Lecture Notes in Computer Science, Springer International Publishing, Cham, pp. 211–227.

Logic and model checking by imprecise probabilistic interpreted systems

@INPROCEEDINGS{antonucci2021d,
   title = {Logic and model checking by imprecise probabilistic interpreted systems},
   editor = {Rosenfeld, A. and Talmon, N.},
   publisher = {Springer International Publishing},
   address = {Cham},
   booktitle = {Multi-Agent Systems. {EUMAS} 2021. Lecture Notes in Computer Science},
   author = {Termine, A. and Antonucci, A. and Primiero, G. and Facchini, A.},
   pages = {211--227},
   year = {2021},
   doi = {10.1007/978-3-030-82254-5_13},
   url = {}
}
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Termine, A., Antonucci, A., Facchini, A., Primiero, G. (2021). Robust model checking with imprecise markov reward models. In De Bock, J., Cano, A., Miranda, E., Moral, S. (Ed), ISIPTA 2021, Proceedings of Machine Learning Research 147, JMLR.org, pp. 299–309.

Robust model checking with imprecise markov reward models

@INPROCEEDINGS{antonucci2021a,
   title = {Robust model checking with imprecise markov reward models},
   editor = {De Bock, J., Cano, A., Miranda, E., Moral, S.},
   publisher = {JMLR.org},
   series = {Proceedings of Machine Learning Research},
   volume = {147},
   booktitle = {{ISIPTA} 2021},
   author = {Termine, A. and Antonucci, A. and Facchini, A. and Primiero, G.},
   pages = {299--309},
   year = {2021},
   doi = {},
   url = {https://proceedings.mlr.press/v147/termine21a.html}
}
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Zaffalon, M., Antonucci, A., Cabañas, R. (2021). Causal expectation-maximisation. In WHY-21 @ NeurIPS 2021.

Causal expectation-maximisation

@INPROCEEDINGS{zaffalon2021c,
   title = {Causal expectation-maximisation},
   booktitle = {{WHY}-21 @ {NeurIPS} 2021},
   author = {Zaffalon, M. and Antonucci, A. and Cabañas, R.},
   year = {2021},
   doi = {},
   url = {https://why21.causalai.net/papers/WHY21_52.pdf}
}
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Zaffalon, M., Miranda, E. (2021). Desirability foundations of robust rational decision making. Synthese 198(27), pp. S6529–S6570.

Desirability foundations of robust rational decision making

@ARTICLE{zaffalon2019a,
   title = {Desirability foundations of robust rational decision making},
   journal = {Synthese},
   publisher = {Springer},
   volume = {198},
   author = {Zaffalon, M. and Miranda, E.},
   number = {27},
   pages = {S6529--S6570},
   year = {2021},
   doi = {10.1007/s11229-018-02010-x},
   url = {}
}
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Zaffalon, M., Miranda, E. (2021). The sure thing. In De Bock, J., Cano, A., Miranda, E., Moral, S. (Ed), ISIPTA 2021, PMLR 147, JMLR.org, pp. 342–351.

The sure thing

@INPROCEEDINGS{zaffalon2021a,
   title = {The sure thing},
   editor = {De Bock, J., Cano, A., Miranda, E., Moral, S.},
   publisher = {JMLR.org},
   series = {PMLR},
   volume = {147},
   booktitle = {{ISIPTA} 2021},
   author = {Zaffalon, M., Miranda, E.},
   pages = {342--351},
   year = {2021},
   doi = {},
   url = {https://www.sipta.org/isipta21/pmlr/zaffalon21.pdf}
}
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Zhu, M., Bemporad, A., Piga, D. (2021). Preference-based MPC calibration. In 2021 European Control Conference (ECC), Napoli, Italy, pp. 638–645.

Preference-based MPC calibration

@INPROCEEDINGS{piga2021e,
   title = {Preference-based {MPC} calibration},
   address = {Napoli, Italy},
   booktitle = {2021 European Control Conference ({ECC})},
   author = {Zhu, M. and Bemporad, A. and Piga, D.},
   pages = {638--645},
   year = {2021},
   doi = {10.23919/ECC54610.2021.9654900},
   url = {}
}
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top

2020

Akata, Z., Ballier, D., de Rijke, M., Dignum, F., Dignum, V., Eiben, G., Fokkens, A., Grossi, D., Hindriks, K., Hoos, H., Hung, H., Jonker, C., Monz, C., Neerincx, M., Oliehoek, F., Prakken, H., Schlobach, S., van der Gaag, L.C., van Harmelen, F., van Hoof, H., van Riemsdijk, B., van Wynsberghe, A., Verbrugge, R., Berheij, B., Vossen, P., Welling, M. (2020). A research agenda for hybrid intelligence: Augmenting human intellect with collaborative, adaptive, responsible and explainable artificial intelligence. IEEE Computer 53, pp. 18–28.

A research agenda for hybrid intelligence: Augmenting human intellect with collaborative, adaptive, responsible and explainable artificial intelligence

@ARTICLE{Linda2020b,
   title = {A research agenda for hybrid intelligence: {A}ugmenting human intellect with collaborative, adaptive, responsible and explainable artificial intelligence},
   journal = {{IEEE} Computer},
   volume = {53},
   author = {Akata, Z. and Ballier, D. and de Rijke, M. and Dignum, F. and Dignum, V. and Eiben, G. and Fokkens, A. and Grossi, D. and Hindriks, K. and Hoos, H. and Hung, H. and Jonker, C. and Monz, C. and Neerincx, M. and Oliehoek, F. and Prakken, H. and Schlobach, S. and van der Gaag, L.C. and van Harmelen, F. and van Hoof, H. and van Riemsdijk, B. and van Wynsberghe, A. and Verbrugge, R. and Berheij, B. and Vossen, P. and Welling, M.},
   pages = {18--28},
   year = {2020},
   doi = {10.1109/MC.2020.2996587},
   url = {}
}
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Antonucci, A., Tiotto, T. (2020). Approximate MMAP by marginal search. In Brawner, K.W., Barták, R., Bell, E. (Eds), Proceedings of the Thirty-third International Florida Artificial Intelligence Research Society Conference (FLAIRS-33), AAAI Press, North Miami Beach, Florida, USA, pp. 181–184.

Approximate MMAP by marginal search

@INPROCEEDINGS{antonucci2020a,
   title = {Approximate {MMAP} by marginal search},
   editor = {Brawner, K.W. and Bart\'ak, R. and Bell, E.},
   publisher = {AAAI Press},
   address = {North Miami Beach, Florida, USA},
   booktitle = {Proceedings of the Thirty-{t}hird International Florida Artificial Intelligence Research Society Conference ({FLAIRS}-33)},
   author = {Antonucci, A. and Tiotto, T.},
   pages = {181--184},
   year = {2020},
   doi = {},
   url = {}
}
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Azzimonti, L., Corani, G., Scutari, M. (2020). Structure learning from related data sets with a hierarchical Bayesian score. In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM 2020) 138, PMLR, pp. 5–16.

Structure learning from related data sets with a hierarchical Bayesian score

@INPROCEEDINGS{azzimonti2020a,
   title = {Structure learning from related data sets with a hierarchical {B}ayesian score},
   publisher = {PMLR},
   volume = {138},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {Azzimonti, L. and Corani, G. and Scutari, M.},
   pages = {5--16},
   year = {2020},
   doi = {},
   url = {http://proceedings.mlr.press/v138/azzimonti20a.html}
}
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Azzimonti, D., Rottondi, C., Giusti, A., Tornatore, M., Bianco, A. (2020). Active vs transfer learning approaches for qot estimation with small training datasets. In Optical Fiber Communication Conference (OFC 2020), Optical Society of America, M4E.1.

Active vs transfer learning approaches for qot estimation with small training datasets

@INPROCEEDINGS{azzimontid2020b,
   title = {Active vs transfer learning approaches for qot estimation with small training datasets},
   publisher = {Optical Society of America},
   booktitle = {Optical Fiber Communication Conference ({OFC} 2020)},
   author = {Azzimonti, D. and Rottondi, C. and Giusti, A. and Tornatore, M. and Bianco, A.},
   pages = {M4E.1},
   year = {2020},
   doi = {10.1364/OFC.2020.M4E.1},
   url = {}
}
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Azzimonti, D., Rottondi, C., Tornatore, M. (2020). Reducing probes for quality of transmission estimation in optical networks with active learning. J. Opt. Commun. Netw. 12(1), pp. A38–A48.

Reducing probes for quality of transmission estimation in optical networks with active learning

@ARTICLE{azzimontid2020a,
   title = {Reducing probes for quality of transmission estimation in optical networks with active learning},
   journal = {J. Opt. Commun. Netw.},
   publisher = {OSA},
   volume = {12},
   author = {Azzimonti, D. and Rottondi, C. and Tornatore, M.},
   number = {1},
   pages = {A38--A48},
   year = {2020},
   doi = {10.1364/JOCN.12.000A38},
   url = {}
}
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Benavoli, A., Azzimonti, D., Piga, D. (2020). Skew gaussian processes for classification. Machine Learning 109(9), pp. 1877–1902.

Skew gaussian processes for classification

@ARTICLE{azzimontid2020c,
   title = {Skew gaussian processes for classification},
   journal = {Machine Learning},
   volume = {109},
   author = {Benavoli, A. and Azzimonti, D. and Piga, D.},
   number = {9},
   pages = {1877--1902},
   year = {2020},
   doi = {10.1007/s10994-020-05906-3},
   url = {}
}
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Bodewes, T., Scutari, M. (2020). Identifiability and consistency of bayesian network structure learning from incomplete data. Proceedings of Machine Learning Research (PGM 2020) 138, pp. 29–40.

Identifiability and consistency of bayesian network structure learning from incomplete data

@ARTICLE{scutari20c,
   title = {Identifiability and consistency of bayesian network structure learning from incomplete data},
   journal = {Proceedings of Machine Learning Research ({PGM} 2020)},
   volume = {138},
   author = {Bodewes, T. and Scutari, M.},
   pages = {29--40},
   year = {2020},
   doi = {},
   url = {https://proceedings.mlr.press/v138/bodewes20a.html}
}
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Bregoli, A., Scutari, M., Stella, F. (2020). Constraint-based learning for continuous-time bayesian networks. Proceedings of Machine Learning Research (PGM 2020) 138, pp. 41–52.

Constraint-based learning for continuous-time bayesian networks

@ARTICLE{scutari20g,
   title = {Constraint-based learning for continuous-time bayesian networks},
   journal = {Proceedings of Machine Learning Research ({PGM} 2020)},
   volume = {138},
   author = {Bregoli, A. and Scutari, M. and Stella, F.},
   pages = {41--52},
   year = {2020},
   doi = {},
   url = {}
}
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Breschi, V., Mejari, M. (2020). Shrinkage strategies for structure selection and identification of piecewise affine models. In 2020 59th Ieee Conference on Decision and Control (cdc), pp. 1626–1631.

Shrinkage strategies for structure selection and identification of piecewise affine models

@INPROCEEDINGS{mejari2020d,
   title = {Shrinkage strategies for structure selection and identification of piecewise affine models},
   booktitle = {2020 59th Ieee Conference on Decision and Control ({c}dc)},
   author = {Breschi, V. and Mejari, M.},
   pages = {1626--1631},
   year = {2020},
   doi = {10.1109/CDC42340.2020.9303927},
   url = {}
}
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Briganti, G., Scutari, M., Linkowski, P. (2020). A machine learning approach to relationships among alexithymia components. Psychiatria Danubina 32(Suppl. 1), pp. 180–187.

A machine learning approach to relationships among alexithymia components

@ARTICLE{scutari20e,
   title = {A machine learning approach to relationships among alexithymia components},
   journal = {Psychiatria Danubina},
   volume = {32},
   author = {Briganti, G. and Scutari, M. and Linkowski, P.},
   number = {Suppl. 1},
   pages = {180--187},
   year = {2020},
   doi = {},
   url = {}
}
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Cabañas, R., Antonucci, A., Huber, D., Zaffalon, M. (2020). Credici: a java library for causal inference by credal networks. In Proceedings of the 10th International Conference on Probabilistic Graphical Models, Proceedings of Machine Learning Research, PMLR, Aalborg, Denmark.

Credici: a java library for causal inference by credal networks

@INPROCEEDINGS{cabanas2020a,
   title = {Credici: a java library for causal inference by credal networks},
   publisher = {PMLR},
   address = {Aalborg, Denmark},
   series = {Proceedings of Machine Learning Research},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models},
   author = {Caba\~nas, R. and Antonucci, A. and Huber, D. and Zaffalon, M.},
   year = {2020},
   doi = {},
   url = {}
}
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Cabañas, R., Cózar, J., Salmerón, A., Masegosa, A.R. (2020). Probabilistic graphical models with neural networks in inferpy. In Proceedings of the 10th International Conference on Probabilistic Graphical Models, Proceedings of Machine Learning Research 138, PMLR, Aalborg, Denmark, pp. 601–604.

Probabilistic graphical models with neural networks in inferpy

@INPROCEEDINGS{cabanas2020b,
   title = {Probabilistic graphical models with neural networks in inferpy},
   publisher = {PMLR},
   address = {Aalborg, Denmark},
   series = {Proceedings of Machine Learning Research},
   volume = {138},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models},
   author = {Caba\~nas, R. and C\'ozar, J. and Salmer\'on, A. and Masegosa, A.R.},
   pages = {601--604},
   year = {2020},
   doi = {},
   url = {https://proceedings.mlr.press/v138/cabanas20b}
}
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Cannelli, L., Facchinei, F., Scutari, G., Kungurtsev, V. (2020). Asynchronous optimization over graphs: linear convergence under error bound conditions. IEEE Transactions on Automatic Control 66(10), pp. 4604–4619.

Asynchronous optimization over graphs: linear convergence under error bound conditions

@ARTICLE{cannelli2020a,
   title = {Asynchronous optimization over graphs: linear convergence under error bound conditions},
   journal = {{IEEE} Transactions on Automatic Control},
   volume = {66},
   author = {Cannelli, L. and Facchinei, F. and Scutari, G. and Kungurtsev, V.},
   number = {10},
   pages = {4604--4619},
   year = {2020},
   doi = {10.1109/TAC.2020.3033490},
   url = {}
}
Download
Casanova, A., Miranda, E., Zaffalon, M. (2020). Social pooling of beliefs and values with desirability. Proceedings of the 33rd International Flairs Conference (FLAIRS-33).

Social pooling of beliefs and values with desirability

@ARTICLE{casanova2020a,
   title = {Social pooling of beliefs and values with desirability},
   journal = {Proceedings of the 33rd International Flairs Conference ({FLAIRS}-33)},
   author = {Casanova, A. and Miranda, E. and Zaffalon, M.},
   year = {2020},
   doi = {},
   url = {https://www.flairs-33.info/}
}
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Coletti, G., van der Gaag, L.C., Petturiti, D., Vantaggi, B. (2020). Detecting correlation between extreme probability events. International Journal of General Systems 49(1), pp. 64–87.

Detecting correlation between extreme probability events

@ARTICLE{Linda2019e,
   title = {Detecting correlation between extreme probability events},
   journal = {International Journal of General Systems },
   volume = {49},
   author = {Coletti, G. and van der Gaag, L.C. and Petturiti, D. and Vantaggi, B.},
   number = {1},
   pages = {64--87},
   year = {2020},
   doi = {10.1080/03081079.2019.1692005},
   url = {}
}
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Corani, G., Azzimonti, D., Augusto, J.P.S.C., Zaffalon, M. (2020). Probabilistic reconciliation of hierarchical forecast via Bayes’ rule. In Hutter, Frank, Kersting, Kristian, Lijffijt, Jefrey, Valera, Isabel (Eds), Joint European Conference on Machine Learning and Knowledge Discovery in Database (ECML- PKDD), Springer International Publishing, pp. 211–226.

Probabilistic reconciliation of hierarchical forecast via Bayes’ rule

@INPROCEEDINGS{corani2020a,
   title = {Probabilistic reconciliation of hierarchical forecast via {B}ayes’ rule},
   editor = {Hutter, Frank and Kersting, Kristian and Lijffijt, Jefrey and Valera, Isabel},
   publisher = {Springer International Publishing},
   booktitle = {Joint European Conference on Machine Learning and Knowledge Discovery in Database ({ECML}- {PKDD})},
   author = {Corani, G. and Azzimonti, D. and Augusto, J.P.S.C. and Zaffalon, M.},
   pages = {211--226},
   year = {2020},
   doi = {10.1007/978-3-030-67664-3_13},
   url = {}
}
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Cózar, J., Cabañas, R., Salmerón, A., Masegosa, A.R. (2020). Inferpy: probabilistic modeling with deep neural networks made easy. Neurocomputing 415, pp. 408–410.

Inferpy: probabilistic modeling with deep neural networks made easy

@ARTICLE{cabanas2020c,
   title = {Inferpy: probabilistic modeling with deep neural networks made easy},
   journal = {Neurocomputing},
   volume = {415},
   author = {C\'ozar, J. and Caba\~nas, R. and Salmer\'on, A. and Masegosa, A.R.},
   pages = {408--410},
   year = {2020},
   doi = {10.1016/j.neucom.2020.07.117},
   url = {}
}
Download
Fisher, H., Gittoes, M., Evans, L., Bitchell, L., Mullen, R., Scutari, M. (2020). An interdisciplinary examination of stress and injury occurrence in athletes. Frontiers in Sports and Active Living 2, 595619.

An interdisciplinary examination of stress and injury occurrence in athletes

@ARTICLE{scutari20f,
   title = {An interdisciplinary examination of stress and injury occurrence in athletes},
   journal = {Frontiers in Sports and Active Living},
   volume = {2},
   author = {Fisher, H. and Gittoes, M. and Evans, L. and Bitchell, L. and Mullen, R. and Scutari, M.},
   pages = {595619},
   year = {2020},
   doi = {10.3389/fspor.2020.595619},
   url = {}
}
Download
Forgione, M., Piga, D. (2020). Model structures and fitting criteria for system identification with neural networks. In Proceedings of the 14th IEEE International Conference Application of Information and Communication Technologies (AICT 20).

Model structures and fitting criteria for system identification with neural networks

@INPROCEEDINGS{forgione2020b,
   title = {Model structures and fitting criteria for system identification with neural networks},
   booktitle = {Proceedings of the 14th {IEEE} International Conference Application of Information and Communication Technologies ({AICT} 20)},
   author = {Forgione, M. and Piga, D.},
   year = {2020},
   doi = {},
   url = {}
}
Download
Forgione, M., Piga, D., Bemporad, A. (2020). Efficient Calibration of Embedded MPC. In Proceedings of the 21st IFAC World Congress (IFAC 20) 53(2), pp. 5189–5194.

Efficient Calibration of Embedded MPC

@INPROCEEDINGS{forgione2020a,
   title = {Efficient {C}alibration of {E}mbedded {MPC}},
   journal = {{IFAC}-{PapersOnLine}},
   volume = {53},
   booktitle = {Proceedings of the 21st {IFAC} World Congress ({IFAC} 20)},
   author = {Forgione, M. and Piga, D. and Bemporad, A.},
   number = {2},
   pages = {5189--5194},
   year = {2020},
   doi = {10.1016/j.ifacol.2020.12.1188},
   url = {}
}
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van der Gaag, L.C., Bolt, J.H. (2020). Poset representations for sets of elementary triplets. In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM 2020) 138, JMLR.org, pp. 521–532.

Poset representations for sets of elementary triplets

@INPROCEEDINGS{Linda2020c,
   title = {Poset representations for sets of elementary triplets},
   publisher = {JMLR.org},
   volume = {138},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {van der Gaag, L.C. and Bolt, J.H.},
   pages = {521--532},
   year = {2020},
   doi = {},
   url = {https://pgm2020.cs.aau.dk/index.php/accepted-papers/}
}
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van der Gaag, L.C., Renooij, S., Facchini, A. (2020). Building causal interaction models by recursive unfolding. In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM 2020) 138, JMLR.org, pp. 509–520.

Building causal interaction models by recursive unfolding

@INPROCEEDINGS{Linda2020a,
   title = {Building causal interaction models by recursive unfolding},
   publisher = {JMLR.org},
   volume = {138},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {van der Gaag, L.C. and Renooij, S. and Facchini, A.},
   pages = {509--520},
   year = {2020},
   doi = {},
   url = {https://proceedings.mlr.press/v138/van-der-gaag20a.html}
}
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Geh, R., Mauá, D.D., Antonucci, A. (2020). Learning probabilistic sentential decision diagrams by sampling. In Proceedings of the Eight Symposium on Knowledge Discovery, Mining and Learning (KMILE 2020), SBC, Porto Alegre, RS, Brasil, pp. 129–136.

Learning probabilistic sentential decision diagrams by sampling

@INPROCEEDINGS{antonucci2020c,
   title = {Learning probabilistic sentential decision diagrams by sampling},
   publisher = {SBC},
   address = {Porto Alegre, RS, Brasil},
   booktitle = {Proceedings of the Eight Symposium on Knowledge Discovery, Mining and Learning ({KMILE} 2020)},
   author = {Geh, R. and Mau\'a, D.D. and Antonucci, A.},
   pages = {129--136},
   year = {2020},
   doi = {10.5753/kdmile.2020.11968},
   url = {}
}
Download
Huber, D., Cabañas, R., Antonucci, A., Zaffalon, M. (2020). CREMA: a Java library for credal network inference. In Jaeger, M., Nielsen, T.D. (Eds), Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM 2020), Proceedings of Machine Learning Research 138, PMLR, Aalborg, Denmark, pp. 613–616.

CREMA: a Java library for credal network inference

@INPROCEEDINGS{huber2020a,
   title = {{CREMA}: a {J}ava library for credal network inference},
   editor = {Jaeger, M. and Nielsen, T.D.},
   publisher = {PMLR},
   address = {Aalborg, Denmark},
   series = {Proceedings of Machine Learning Research},
   volume = {138},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {Huber, D. and Caba\~nas, R. and Antonucci, A. and Zaffalon, M.},
   pages = {613--616},
   year = {2020},
   doi = {},
   url = {https://pgm2020.cs.aau.dk}
}
Download
Kanjirangat, V., Mellace, S., Antonucci, A. (2020). Temporal embeddings and transformer models for narrative text understanding. In Third International Workshop on Narrative Extraction from Texts (Text2Story 20), 42nd European Conference on Information Retrieval (ECIR 20), ceur.

Temporal embeddings and transformer models for narrative text understanding

@INPROCEEDINGS{vani2020b,
   title = {Temporal embeddings and transformer models for narrative text understanding},
   publisher = {ceur},
   booktitle = {Third International Workshop on Narrative Extraction {f}rom Texts ({Text2Story} 20), 42nd European Conference on Information Retrieval ({ECIR} 20)},
   author = {Kanjirangat, V. and Mellace, S. and Antonucci, A.},
   year = {2020},
   doi = {},
   url = {http://ceur-ws.org/Vol-2593/paper9.pdf}
}
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Kanjirangat, V., Mitrovic, S., Antonucci, A., Rinaldi, F. (2020). SST-BERT at SemEval-2020 task 1: semantic shift tracing by clustering in BERT-based embedding spaces. In SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection.To appear In Proceedings of the 14th International Workshop on Semantic Evaluation, Barcelona, Spain, pp. 214–221.

SST-BERT at SemEval-2020 task 1: semantic shift tracing by clustering in BERT-based embedding spaces

@INPROCEEDINGS{vani2020semeval,
   title = {{SST}-{BERT} at {SemEval}-2020 task 1: semantic shift tracing by clustering in {BERT}-based embedding spaces},
   booktitle = {{SemEval}-2020 Task 1: Unsupervised Lexical Semantic Change Detection.To {a}ppear In Proceedings of the 14th International Workshop on Semantic Evaluation, Barcelona, Spain},
   author = {Kanjirangat, V. and Mitrovic, S. and Antonucci, A. and Rinaldi, F.},
   pages = {214--221},
   year = {2020},
   doi = {10.18653/v1/2020.semeval-1.26},
   url = {}
}
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Kern, H., Corani, G., Huber, D., Vermes, N., Zaffalon, M., Varini, M., Wenzel, C., Fringer, A. (2020). Impact on place of death in cancer patients: a causal exploration in southern switzerland. BMC Palliative Care 19, 160.

Impact on place of death in cancer patients: a causal exploration in southern switzerland

@ARTICLE{Kern2020,
   title = {Impact on place of death in cancer patients: a causal exploration in southern switzerland},
   journal = {{BMC} Palliative Care},
   publisher = {Research Square},
   volume = {19},
   author = {Kern, H. and Corani, G. and Huber, D. and Vermes, N. and Zaffalon, M. and Varini, M. and Wenzel, C. and Fringer, A.},
   pages = {160},
   year = {2020},
   doi = {10.21203/rs.3.rs-29758/v3},
   url = {}
}
Download
Laurain, V., Tóth, R., Piga, D., Darwish, M.A.H. (2020). Sparse RKHS estimation via globally convex optimization and its application in LPV-IO identification. Automatica 115, 108914.

Sparse RKHS estimation via globally convex optimization and its application in LPV-IO identification

@ARTICLE{piga2020b,
   title = {Sparse {RKHS} estimation via globally convex optimization and its application in {LPV}-{IO} identification},
   journal = {Automatica},
   volume = {115},
   author = {Laurain, V. and T\'oth, R. and Piga, D. and Darwish, M.A.H.},
   pages = {108914},
   year = {2020},
   doi = {10.1016/j.automatica.2020.108914},
   url = {}
}
Download
Liew, B.X.W., Peolsson, A., Scutari, M., Löfgren, H., Wibault, J., r A Dedering, , Öberg, B., Zsigmond, P., Falla, D. (2020). Probing the mechanisms underpinning recovery in post-surgical patients with cervical radiculopathy using bayesian networks. European Journal of Pain 24(5), pp. 909–920.

Probing the mechanisms underpinning recovery in post-surgical patients with cervical radiculopathy using bayesian networks

@ARTICLE{scutari20a,
   title = {Probing the mechanisms underpinning recovery in post-surgical patients with cervical radiculopathy using bayesian networks},
   journal = {European Journal of Pain},
   volume = {24},
   author = {Liew, B.X.W. and Peolsson, A. and Scutari, M. and L\"ofgren, H. and Wibault, J. and r A Dedering, and \"Oberg, B. and Zsigmond, P. and Falla, D.},
   number = {5},
   pages = {909--920},
   year = {2020},
   doi = {10.1002/ejp.1537},
   url = {}
}
Download
Mangili, F., Broggini, D., Antonucci, A. (2020). Conversational recommender system by Bayesian methods. In Davis, Jesse, Tabia, Karim (Eds), Proceedings of the Fourteenth International Conference on Scalable Uncertainty Management (SUM 2020), Lecture Notes in Artificial Intelligence 12322, Springer, Cham, pp. 200–213.

Conversational recommender system by Bayesian methods

@INPROCEEDINGS{mangili2020b,
   title = {Conversational recommender system by {B}ayesian methods},
   editor = {Davis, Jesse and Tabia, Karim},
   publisher = {Springer, Cham},
   series = {Lecture Notes in Artificial Intelligence},
   volume = {12322},
   booktitle = {Proceedings of the Fourteenth International Conference on Scalable Uncertainty Management ({SUM} 2020)},
   author = {Mangili, F. and Broggini, D. and Antonucci, A.},
   pages = {200--213},
   year = {2020},
   doi = {10.1007/978-3-030-58449-8_14},
   url = {}
}
Download
Mangili, F., Broggini, D., Antonucci, A., Alberti, M., Cimasoni, L. (2020). A Bayesian approach to conversational recommendation systems. AAAI 2020 Workshop on Interactive and Conversational Recommendation Systems (WICRS-20).

A Bayesian approach to conversational recommendation systems

@ARTICLE{mangili2020a,
   title = {A {B}ayesian approach to conversational recommendation systems},
   journal = {{AAAI} 2020 Workshop on Interactive and Conversational Recommendation Systems ({WICRS}-20)},
   author = {Mangili, F. and Broggini, D. and Antonucci, A. and Alberti, M. and Cimasoni, L.},
   year = {2020},
   doi = {},
   url = {https://sites.google.com/view/wicrs2020}
}
Download
Mattei, L., Antonucci, A., Mauá, D.D., Facchini, A., Llerena, J.V. (2020). Tractable inference in credal sentential decision diagrams. International Journal of Approximate Reasoning 125, pp. 26–48.

Tractable inference in credal sentential decision diagrams

@ARTICLE{antonucci2020d,
   title = {Tractable inference in credal sentential decision diagrams},
   journal = {International Journal of Approximate Reasoning},
   volume = {125},
   author = {Mattei, L. and Antonucci, A. and Mau\'a, D.D. and Facchini, A. and Llerena, J.V.},
   pages = {26--48},
   year = {2020},
   doi = {10.1016/j.ijar.2020.06.005},
   url = {}
}
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Mauà, D.D., Ribeiro, H., Katague, G., Antonucci, A. (2020). Two reformulation approaches to maximum-a-posteriori inference in sum-product networks. In Jaeger, M., Nielsen, T.D. (Eds), Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM 2020), Proceedings of Machine Learning Research 138, PMLR, Aalborg, Denmark, pp. 293–304.

Two reformulation approaches to maximum-a-posteriori inference in sum-product networks

@INPROCEEDINGS{antonucci2020b,
   title = {Two reformulation approaches to maximum-a-posteriori inference in sum-product networks},
   editor = {Jaeger, M. and Nielsen, T.D.},
   publisher = {PMLR},
   address = {Aalborg, Denmark},
   series = {Proceedings of Machine Learning Research},
   volume = {138},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {Mau\`a, D.D. and Ribeiro, H. and Katague, G. and Antonucci, A.},
   pages = {293--304},
   year = {2020},
   doi = {},
   url = {https://proceedings.mlr.press/v138/maua20a.html}
}
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Mejari, M., Breschi, V., Naik, V.V., Piga, D. (2020). A bias-correction approach for the identification of piecewise affine output-error models. In 21st IFAC World Congress (IFAC 2020) 53(2), Berlin, Germany, pp. 1096–1101.

A bias-correction approach for the identification of piecewise affine output-error models

@INPROCEEDINGS{mejari2020a,
   title = {A bias-correction approach for the identification of piecewise affine output-error models},
   journal = {{IFAC}-{PapersOnLine}},
   address = {Berlin, Germany},
   volume = {53},
   booktitle = {21st {IFAC} World Congress ({IFAC} 2020)},
   author = {Mejari, M. and Breschi, V. and Naik, V.V. and Piga, D.},
   number = {2},
   pages = {1096--1101},
   year = {2020},
   doi = {10.1016/j.ifacol.2020.12.1307},
   url = {https://www.ifac2020.org}
}
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Mejari, M., Breschi, V., Piga, D. (2020). Recursive bias-correction method for identification of piecewise affine output-error models. IEEE Control Systems Letters 4, pp. 970–975.

Recursive bias-correction method for identification of piecewise affine output-error models

@ARTICLE{mejari2020b,
   title = {Recursive bias-correction method for identification of piecewise affine output-error models},
   journal = {{IEEE} Control Systems Letters},
   volume = {4},
   author = {Mejari, M. and Breschi, V. and Piga, D.},
   pages = {970--975},
   year = {2020},
   doi = {10.1109/LCSYS.2020.2998282},
   url = {}
}
Download
Mejari, M., Naik, V.V., Piga, D., Bemporad, A. (2020). Identification of hybrid and linear parameter-varying models via piecewise affine regression using mixed integer programming. International Journal of Robust and Nonlinear Control 30(15), pp. 5802–5819.

Identification of hybrid and linear parameter-varying models via piecewise affine regression using mixed integer programming

@ARTICLE{mejari2020c,
   title = {Identification of hybrid and linear parameter-varying models via piecewise affine regression using mixed integer programming},
   journal = {International Journal of Robust and Nonlinear Control},
   volume = {30},
   author = {Mejari, M. and Naik, V.V. and Piga, D. and Bemporad, A.},
   number = {15},
   pages = {5802--5819},
   year = {2020},
   doi = {https://doi.org/10.1002/rnc.5198},
   url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/rnc.5198}
}
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Miranda, E., Zaffalon, M. (2020). Compatibility, desirability, and the running intersection property. Artificial Intelligence 283, 103724.

Compatibility, desirability, and the running intersection property

@ARTICLE{zaffalon2020a,
   title = {Compatibility, desirability, and the running intersection property},
   journal = {Artificial Intelligence},
   volume = {283},
   author = {Miranda, E., Zaffalon, M.},
   pages = {103724},
   year = {2020},
   doi = {10.1016/j.artint.2020.103274},
   url = {}
}
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Piga, D., Bemporad, A., Benavoli, A. (2020). Rao-Blackwellized sampling for batch and recursive Bayesian inference of piecewise affine models. Automatica 117, 109002.

Rao-Blackwellized sampling for batch and recursive Bayesian inference of piecewise affine models

@ARTICLE{piga2020a,
   title = {Rao-{B}lackwellized sampling for batch and recursive {B}ayesian inference of piecewise affine models},
   journal = {Automatica},
   volume = {117},
   author = {Piga, D. and Bemporad, A. and Benavoli, A.},
   pages = {109002},
   year = {2020},
   doi = {10.1016/j.automatica.2020.109002},
   url = {}
}
Download
Piga, D., Breschi, V., Bemporad, A. (2020). Estimation of jump box–jenkins models. Automatica 120, 109126.

Estimation of jump box–jenkins models

@ARTICLE{piga2020c,
   title = {Estimation of jump box--jenkins models},
   journal = {Automatica},
   volume = {120},
   author = {Piga, D. and Breschi, V. and Bemporad, A.},
   pages = {109126},
   year = {2020},
   doi = {10.1016/j.automatica.2020.109126},
   url = {http://www.sciencedirect.com/science/article/pii/S0005109820303241}
}
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Roveda, L., Bussolan, A., Braghin, F., Piga, D. (2020). 6D virtual sensor for wrench estimation in robotized interaction tasks exploiting extended Kalman filter. MDPI Machines 8(4), 67.

6D virtual sensor for wrench estimation in robotized interaction tasks exploiting extended Kalman filter

@ARTICLE{Roveda2020b,
   title = {{6D} virtual sensor for wrench estimation in robotized interaction tasks exploiting extended {K}alman filter},
   journal = {{MDPI} Machines},
   volume = {8},
   author = {Roveda, L. and Bussolan, A. and Braghin, F. and Piga, D.},
   number = {4},
   pages = {67},
   year = {2020},
   doi = {10.3390/machines8040067},
   url = {}
}
Download
Roveda, L., Castaman, N., Franceschi, P., Ghidoni, S., Pedrocchi, N. (2020). A control framework definition to overcome position/interaction dynamics uncertainties in force-controlled tasks. In IEEE International Conference on Robotics and Automation (ICRA) 2020, pp. 6819–6825.

A control framework definition to overcome position/interaction dynamics uncertainties in force-controlled tasks

@INPROCEEDINGS{Roveda2020f,
   title = {A control framework definition to overcome position/interaction dynamics uncertainties in force-controlled tasks},
   booktitle = {{IEEE} International Conference on Robotics and Automation ({ICRA}) 2020},
   author = {Roveda, L. and Castaman, N. and Franceschi, P. and Ghidoni, S. and Pedrocchi, N.},
   pages = {6819--6825},
   year = {2020},
   doi = {10.1109/ICRA40945.2020.9197141},
   url = {}
}
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Roveda, L., Forgione, M., Piga, D. (2020). Robot control parameters auto-tuning in trajectory tracking applications. Control Engineering Practice 101, 104488.

Robot control parameters auto-tuning in trajectory tracking applications

@ARTICLE{roveda2020a,
   title = {Robot control parameters auto-tuning in trajectory tracking applications},
   journal = {Control Engineering Practice},
   volume = {101},
   author = {Roveda, L. and Forgione, M. and Piga, D.},
   pages = {104488},
   year = {2020},
   doi = {10.1016/j.conengprac.2020.104488},
   url = {}
}
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Roveda, L., Forgione, M., Piga, D. (2020). One-stage auto-tuning procedure of robot dynamics and control parameters for trajectory tracking applications. In Ubiquitous Robots 2020, pp. 105–112.

One-stage auto-tuning procedure of robot dynamics and control parameters for trajectory tracking applications

@INPROCEEDINGS{Roveda2020h,
   title = {One-stage auto-tuning procedure of robot dynamics and control parameters for trajectory tracking applications},
   booktitle = {Ubiquitous Robots 2020},
   author = {Roveda, L. and Forgione, M. and Piga, D.},
   pages = {105--112},
   year = {2020},
   doi = {10.1109/UR49135.2020.9144761},
   url = {}
}
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Roveda, L., Magni, M., Cantoni, M., Piga, D., Bucca, G. (2020). Human–robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian optimization. Robotics and Autonomous Systems 136, 103711.

Human–robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian optimization

@ARTICLE{Roveda2020j,
   title = {Human--robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via {B}ayesian optimization},
   journal = {Robotics and Autonomous Systems},
   volume = {136},
   author = {Roveda, L. and Magni, M. and Cantoni, M. and Piga, D. and Bucca, G.},
   pages = {103711},
   year = {2020},
   doi = {10.1016/j.robot.2020.103711},
   url = {}
}
Download
Roveda, L., Magni, M., Cantoni, M., Piga, D., Bucca, G. (2020). Assembly task learning and optimization through Human’s demonstration and machine learning. In IEEE International Conference on Systems, Man, and Cybernetics, pp. 1852–1859.

Assembly task learning and optimization through Human’s demonstration and machine learning

@INPROCEEDINGS{Roveda2020k,
   title = {Assembly task learning and optimization through {H}uman’s demonstration and machine learning},
   booktitle = {{IEEE} International Conference on Systems, Man, and Cybernetics},
   author = {Roveda, L. and Magni, M. and Cantoni, M. and Piga, D. and Bucca, G.},
   pages = {1852--1859},
   year = {2020},
   doi = {10.1109/SMC42975.2020.9282911},
   url = {}
}
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Roveda, L., Maskani, J., Franceschi, P., Arash, A., Braghin, F., Molinari Tosatti, L., Pedrocchi, N. (2020). Model-based reinforcement learning variable impedance control for human-robot collaboration. Journal of Intelligent & Robotic Systems 100(2), pp. 417–433.

Model-based reinforcement learning variable impedance control for human-robot collaboration

@ARTICLE{Roveda2020c,
   title = {Model-based reinforcement learning variable impedance control for human-robot collaboration},
   journal = {Journal of Intelligent & Robotic Systems},
   publisher = {Springer},
   volume = {100},
   author = {Roveda, L. and Maskani, J. and Franceschi, P. and Arash, A. and Braghin, F. and Molinari Tosatti, L. and Pedrocchi, N.},
   number = {2},
   pages = {417--433},
   year = {2020},
   doi = {10.1007/s10846- 020-01183-3},
   url = {}
}
Download
Roveda, L., Piga, D. (2020). Robust state dependent Riccati equation variable impedance control for robotic force-tracking tasks. International Journal of Intelligent Robotics and Applications 4(4), pp. 507–519.

Robust state dependent Riccati equation variable impedance control for robotic force-tracking tasks

@ARTICLE{Roveda2020d,
   title = {Robust state dependent {R}iccati equation variable impedance control for robotic force-tracking tasks},
   journal = {International Journal of Intelligent Robotics and Applications},
   publisher = {Springer},
   volume = {4},
   author = {Roveda, L. and Piga, D.},
   number = {4},
   pages = {507--519},
   year = {2020},
   doi = {10.1007/s41315-020-00153-0},
   url = {}
}
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Roveda, L., Piga, D. (2020). Interaction force computation exploiting environment stiffness estimation for sensorless robot applications. In IEEE Metrology for Industry 4.0 and IoT 2020, pp. 360–363.

Interaction force computation exploiting environment stiffness estimation for sensorless robot applications

@INPROCEEDINGS{Roveda2020g,
   title = {Interaction force computation exploiting environment stiffness estimation for sensorless robot applications},
   booktitle = {{IEEE} Metrology for Industry 4.0 and {IoT} 2020},
   author = {Roveda, L. and Piga, D.},
   pages = {360--363},
   year = {2020},
   doi = {10.1109/MetroInd4.0IoT48571.2020.9138189},
   url = {}
}
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Roveda, L., Savani, L., Arlati, S., Dinon, T., Legnani, G., Molinari Tosatti, L. (2020). Design methodology of an active back-support exoskeleton with adaptable backbone-based kinematics. International Journal of Industrial Ergonomics 79, 102991.

Design methodology of an active back-support exoskeleton with adaptable backbone-based kinematics

@ARTICLE{Roveda2020e,
   title = {Design methodology of an active back-support exoskeleton with adaptable backbone-based kinematics},
   journal = {International Journal of Industrial Ergonomics},
   publisher = {Elsevier},
   volume = {79},
   author = {Roveda, L. and Savani, L. and Arlati, S. and Dinon, T. and Legnani, G. and Molinari Tosatti, L.},
   pages = {102991},
   year = {2020},
   doi = {10.1016/j.ergon.2020.102991},
   url = {}
}
Download
Ruggieri, A., Stranieri, F., Stella, F., Scutari, M. (2020). Hard and soft em in bayesian network learning from incomplete data. Algorithms 13(12), 329.

Hard and soft em in bayesian network learning from incomplete data

@ARTICLE{scutari20h,
   title = {Hard and soft em in bayesian network learning from incomplete data},
   journal = {Algorithms},
   volume = {13},
   author = {Ruggieri, A. and Stranieri, F. and Stella, F. and Scutari, M.},
   number = {12},
   pages = {329},
   year = {2020},
   doi = {10.3390/a13120329},
   url = {}
}
Download
Schürch, M., Azzimonti, D., Benavoli, A., Zaffalon, M. (2020). Recursive estimation for sparse gaussian process regression. Automatica 120, 109127.

Recursive estimation for sparse gaussian process regression

@ARTICLE{schurch2020a,
   title = {Recursive estimation for sparse gaussian process regression},
   journal = {Automatica},
   publisher = {Elsevier},
   volume = {120},
   author = {Sch\"urch, M. and Azzimonti, D. and Benavoli, A. and Zaffalon, M.},
   pages = {109127},
   year = {2020},
   doi = {10.1016/j.automatica.2020.109127},
   url = {}
}
Download
Shahid, A.A., Roveda, L., Piga, D., Braghin, F. (2020). Learning continuous control actions for robotic grasping with reinforcement learning. In IEEE International Conference on Systems, Man, and Cybernetics, pp. 4066–4072.

Learning continuous control actions for robotic grasping with reinforcement learning

@INPROCEEDINGS{Roveda2020l,
   title = {Learning continuous control actions for robotic grasping with reinforcement learning},
   booktitle = {{IEEE} International Conference on Systems, Man, and Cybernetics},
   author = {Shahid, A.A. and Roveda, L. and Piga, D. and Braghin, F.},
   pages = {4066--4072},
   year = {2020},
   doi = {10.1109/SMC42975.2020.9282951},
   url = {}
}
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Sheldrake, T.E., Caricchi, L., Scutari, M. (2020). Tectonic control on global variations in the record of large-magnitude explosive eruptions in volcanic arcs. Frontiers in Earth Sciences 8(127), pp. 1–14.

Tectonic control on global variations in the record of large-magnitude explosive eruptions in volcanic arcs

@ARTICLE{scutari20b,
   title = {Tectonic control on global variations in the record of large-magnitude explosive eruptions in volcanic arcs},
   journal = {Frontiers in Earth Sciences},
   volume = {8},
   author = {Sheldrake, T.E. and Caricchi, L. and Scutari, M.},
   number = {127},
   pages = {1--14},
   year = {2020},
   doi = {10.3389/feart.2020.00127},
   url = {}
}
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Sorgini, F., Airò Farulla, G., Lukic, N., Danilov, I., Roveda, L., Milivojevic, M., Babu Pulikottil, T., Carrozza, M.C., Prinetto, P., Tolio, T., Oddo, C.M., Petrovic, P., Bojovic, B. (2020). Tactile sensing with gesture-controlled collaborative robot. In 2020 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0 & IoT), pp. 364–368.

Tactile sensing with gesture-controlled collaborative robot

@INPROCEEDINGS{Roveda2020i,
   title = {Tactile sensing with gesture-controlled collaborative robot},
   booktitle = {2020 {IEEE} International Workshop on Metrology for Industry 4.0 & {IoT} ({MetroInd4}.0 & {IoT})},
   author = {Sorgini, F. and Air\`o Farulla, G. and Lukic, N. and Danilov, I. and Roveda, L. and Milivojevic, M. and Babu Pulikottil, T. and Carrozza, M.C. and Prinetto, P. and Tolio, T. and Oddo, C.M. and Petrovic, P. and Bojovic, B.},
   pages = {364--368},
   year = {2020},
   doi = {10.1109/MetroInd4.0IoT48571.2020.9138183},
   url = {}
}
Download
Szehr, O., Zarouf, R. (2020). Interpolation without commutants. Journal of Operator Theory 84(1), pp. 239–256.

Interpolation without commutants

@ARTICLE{szehr2020aa,
   title = {Interpolation without commutants},
   journal = {Journal of Operator Theory},
   volume = {84},
   author = {Szehr, O. and Zarouf, R.},
   number = {1},
   pages = {239--256},
   year = {2020},
   doi = {10.7900/jot.2019may21.2264},
   url = {}
}
Download
Volpetti, C., Kanjirangat, V., Antonucci, A. (2020). Temporal word embeddings for narrative understanding. In 12th International Conference on Machine Learning and Computing (ICMLC 2020) (5), ACM, pp. 68–72.

Temporal word embeddings for narrative understanding

@INPROCEEDINGS{supsi2020a,
   title = {Temporal word embeddings for narrative understanding},
   publisher = {ACM},
   booktitle = {12th International Conference on Machine Learning and Computing ({ICMLC} 2020)},
   author = {Volpetti, C. and Kanjirangat, V. and Antonucci, A.},
   number = {5},
   pages = {68--72},
   year = {2020},
   doi = {10.1145/3383972.3383988},
   url = {}
}
Download
Yoo, J., Kang, U., Scanagatta, M., Corani, G., Zaffalon, M. (2020). Sampling subgraphs with guaranteed treewidth for accurate and efficient graphical inference. In Proceedings of International Conference on Web Search and Data Mining (WSDM '20) (9), pp. 708–16.

Sampling subgraphs with guaranteed treewidth for accurate and efficient graphical inference

@INPROCEEDINGS{corani2019e,
   title = {Sampling subgraphs with guaranteed treewidth for accurate and efficient graphical inference},
   booktitle = {Proceedings of International Conference on Web Search and Data Mining ({WSDM} '20)},
   author = {Yoo, J. and Kang, U. and Scanagatta, M. and Corani, G. and Zaffalon, M.},
   number = {9},
   pages = {708--16},
   year = {2020},
   doi = {10.1145/3336191.3371815},
   url = {}
}
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Zaffalon, M., Antonucci, A., Cabañas, R. (2020). Structural causal models are (solvable by) credal networks. In Jaeger, M., Nielsen, T. D. (Ed), Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM 2020), PMLR 138, JMLR.org, pp. 581–592.

Structural causal models are (solvable by) credal networks

@INPROCEEDINGS{zaffalon2020b,
   title = {Structural causal models are (solvable by) credal networks},
   editor = {Jaeger, M., Nielsen, T. D. },
   publisher = {JMLR.org},
   series = {PMLR},
   volume = {138},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {Zaffalon, M. and Antonucci, A. and Cabañas, R.},
   pages = {581--592},
   year = {2020},
   doi = {},
   url = {http://proceedings.mlr.press/v138/zaffalon20a/zaffalon20a.pdf}
}
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top

2019

Antonucci, A. (2019). Reliable discretisation of deterministic equations in Bayesian networks. In Proceedings of the 32nd International Flairs Conference (FLAIRS-32), AAAI Press.

Reliable discretisation of deterministic equations in Bayesian networks

@INPROCEEDINGS{supsi2019c,
   title = {Reliable discretisation of deterministic equations in {B}ayesian networks},
   publisher = {AAAI Press},
   booktitle = {Proceedings of the 32nd International Flairs Conference ({FLAIRS}-32)},
   author = {Antonucci, A.},
   year = {2019},
   doi = {},
   url = {}
}
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Antonucci, A., Facchini, A., Mattei, L. (2019). Credal sentential decision diagrams. In Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications (ISIPTA '19) 103, PMLR, pp. 14–22.

Credal sentential decision diagrams

@INPROCEEDINGS{supsi2019b,
   title = {Credal sentential decision diagrams},
   publisher = {PMLR},
   volume = {103},
   booktitle = {Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications ({ISIPTA} '19)},
   author = {Antonucci, A. and Facchini, A. and Mattei, L.},
   pages = {14--22},
   year = {2019},
   doi = {},
   url = {https://proceedings.mlr.press/v103/antonucci19a.html}
}
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Arnone, E., Azzimonti, L., Nobile, F., Sangalli, L.M. (2019). Modeling spatially dependent functional data via regression with differential regularization. Journal of Multivariate Analysis 170, pp. 275–295.

Modeling spatially dependent functional data via regression with differential regularization

@ARTICLE{azzimonti2018a,
   title = {Modeling spatially dependent functional data via regression with differential regularization},
   journal = {Journal of Multivariate Analysis},
   volume = {170},
   author = {Arnone, E. and Azzimonti, L. and Nobile, F. and Sangalli, L.M.},
   pages = {275--295},
   year = {2019},
   doi = {10.1016/j.jmva.2018.09.006},
   url = {}
}
Download
Azzimonti, L., Corani, G., Zaffalon, M. (2019). Hierarchical estimation of parameters in Bayesian networks. Computational Statistics and Data Analysis 137, pp. 67–91.

Hierarchical estimation of parameters in Bayesian networks

@ARTICLE{azzimonti2019a,
   title = {Hierarchical estimation of parameters in {B}ayesian networks},
   journal = {Computational Statistics and Data Analysis},
   volume = {137},
   author = {Azzimonti, L. and Corani, G. and Zaffalon, M.},
   pages = {67--91},
   year = {2019},
   doi = {10.1016/j.csda.2019.02.004},
   url = {}
}
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Azzimonti, D., Ginsbourger, D., Chevalier, C., Bect, J., Richet, Y. (2019). Adaptive design of experiments for conservative estimation of excursion sets. Technometrics 63(1), pp. 13–26.

Adaptive design of experiments for conservative estimation of excursion sets

@ARTICLE{azzimontid2019c,
   title = {Adaptive design of experiments for conservative estimation of excursion sets},
   journal = {Technometrics},
   publisher = {Taylor & Francis},
   volume = {63},
   author = {Azzimonti, D. and Ginsbourger, D. and Chevalier, C. and Bect, J. and Richet, Y.},
   number = {1},
   pages = {13--26},
   year = {2019},
   doi = {10.1080/00401706.2019.1693427},
   url = {}
}
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Azzimonti, D., Ginsbourger, D., Rohmer, J., Idier, D. (2019). Profile extrema for visualizing and quantifying uncertainties on excursion regions. Application to coastal flooding. Technometrics 61(4), pp. 474–493.

Profile extrema for visualizing and quantifying uncertainties on excursion regions. Application to coastal flooding

@ARTICLE{azzimontid2019a,
   title = {Profile extrema for visualizing and quantifying uncertainties on excursion regions. Application to coastal flooding},
   journal = {Technometrics},
   publisher = {Taylor & Francis},
   volume = {61},
   author = {Azzimonti, D. and Ginsbourger, D. and Rohmer, J. and Idier, D.},
   number = {4},
   pages = {474--493},
   year = {2019},
   doi = {10.1080/00401706.2018.1562987},
   url = {}
}
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Azzimonti, D., Rottondi, C., Tornatore, M. (2019). Using active learning to decrease probes for QoT estimation in optical networks. In , Optical Society of America, Th1H.1.

Using active learning to decrease probes for QoT estimation in optical networks

@INPROCEEDINGS{azzimontid2019b,
   title = {Using active learning to decrease probes for {QoT} estimation in optical networks},
   journal = {Optical Fiber Communication Conference ({OFC}) 2019},
   publisher = {Optical Society of America},
   author = {Azzimonti, D. and Rottondi, C. and Tornatore, M.},
   pages = {Th1H.1},
   year = {2019},
   doi = {10.1364/OFC.2019.Th1H.1},
   url = {}
}
Download
Benavoli, A., Facchini, A., Zaffalon, M. (2019). Bernstein's socks, polynomial-time provable coherence and entanglement. In De Bock, J., de Campos, C., de Cooman, G., Quaeghebeur, E., Wheeler, G. (Eds), ISIPTA '19: Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications, PMLR 103, JMLR.org, pp. 23–31.

Bernstein's socks, polynomial-time provable coherence and entanglement

@INPROCEEDINGS{zaffalon2019b,
   title = {Bernstein's socks, polynomial-time provable coherence and entanglement},
   editor = {De Bock, J. and de Campos, C. and de Cooman, G. and Quaeghebeur, E. and Wheeler, G.},
   publisher = {JMLR.org},
   series = {PMLR},
   volume = {103},
   booktitle = {{ISIPTA };'19: Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications},
   author = {Benavoli, A. and Facchini, A. and Zaffalon, M.},
   pages = {23--31},
   year = {2019},
   doi = {},
   url = {https://proceedings.mlr.press/v103/benavoli19a.html}
}
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Benavoli, A., Facchini, A., Piga, D., Zaffalon, M. (2019). Sum-of-squares for bounded rationality. International Journal of Approximate Reasoning 105, pp. 130–152.

Sum-of-squares for bounded rationality

@ARTICLE{benavoli2019a,
   title = {Sum-of-squares for bounded rationality},
   journal = {International Journal of Approximate Reasoning},
   volume = {105},
   author = {Benavoli, A., Facchini, A., Piga, D., Zaffalon, M.},
   pages = {130--152},
   year = {2019},
   doi = {10.1016/j.ijar.2018.11.012},
   url = {}
}
Download
Bolt, J.H., van der Gaag, L.C. (2019). On minimum elementary-triplet bases for independence relations. In De Bock, J., de Campos, C.P., de Cooman, G., Quaeghebeur, E., Wheeler, G. (Eds), Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications (ISIPTA '19), PMLR 103, JMLR.org, pp. 32–37.

On minimum elementary-triplet bases for independence relations

@INPROCEEDINGS{Linda2019c,
   title = {On minimum elementary-triplet bases for independence relations},
   editor = {De Bock, J. and de Campos, C.P. and de Cooman, G. and Quaeghebeur, E. and Wheeler, G.},
   publisher = {JMLR.org},
   series = {PMLR},
   volume = {103},
   booktitle = {Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications ({ISIPTA} '19)},
   author = {Bolt, J.H. and van der Gaag, L.C.},
   pages = {32--37},
   year = {2019},
   doi = {},
   url = {https://proceedings.mlr.press/v103/bolt19a.html}
}
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Breschi, V., Piga, D., Bemporad, A. (2019). Online end-use energy disaggregation via jump linear models. Control Engineering Practice 89, pp. 30–42.

Online end-use energy disaggregation via jump linear models

@ARTICLE{piga2019b,
   title = {Online end-use energy disaggregation via jump linear models},
   journal = {Control Engineering Practice},
   volume = {89},
   author = {Breschi, V. and Piga, D. and Bemporad, A.},
   pages = {30--42},
   year = {2019},
   doi = {10.1016/j.conengprac.2019.05.011},
   url = {}
}
Download
Bucher, D., Mangili, F., Cellina, F., Bonesana, C., Jonietz, D., Raubal, M. (2019). From location tracking to personalized eco-feedback: a framework for geographic information collection, processing and visualization to promote sustainable mobility behaviors. Travel Behaviour and Society 14, pp. 43–56.

From location tracking to personalized eco-feedback: a framework for geographic information collection, processing and visualization to promote sustainable mobility behaviors

@ARTICLE{mangili2019a,
   title = { From location tracking to personalized eco-feedback: a framework for geographic information collection, processing and visualization to promote sustainable mobility behaviors},
   journal = {Travel Behaviour and Society},
   volume = {14},
   author = {Bucher, D. and Mangili, F. and Cellina, F. and Bonesana, C. and Jonietz, D. and Raubal, M.},
   pages = {43--56},
   year = {2019},
   doi = {10.1016/j.tbs.2018.09.005},
   url = {}
}
Download
Carollo, V., Piga, D., Borri, C., Paggi, M. (2019). Identification of elasto-plastic and nonlinear fracture mechanics parameters of silver-plated copper busbars for photovoltaics. Engineering Fracture Mechanics 205, pp. 439–454.

Identification of elasto-plastic and nonlinear fracture mechanics parameters of silver-plated copper busbars for photovoltaics

@ARTICLE{piga2019d,
   title = {Identification of elasto-plastic and nonlinear fracture mechanics parameters of silver-plated copper busbars for photovoltaics},
   journal = {Engineering Fracture Mechanics},
   volume = {205},
   author = {Carollo, V. and Piga, D. and Borri, C. and Paggi, M.},
   pages = {439--454},
   year = {2019},
   doi = {10.1016/j.engfracmech.2018.11.014},
   url = {}
}
Download
Cellina, F., Bucher, D., Mangili, F., Simão, J.V., Rudel, R., Raubal, M. (2019). A large scale, app-based behaviour change experiment persuading sustainable mobility patterns: methods, results and lessons learnt. Sustainability 11(9), 2674.

A large scale, app-based behaviour change experiment persuading sustainable mobility patterns: methods, results and lessons learnt

@ARTICLE{mangili2019b,
   title = {A large scale, app-based behaviour change experiment persuading sustainable mobility patterns: methods, results and lessons learnt},
   journal = {Sustainability},
   editor = {mdpi},
   volume = {11},
   author = {Cellina, F. and Bucher, D. and Mangili, F. and Sim\~ao, J.V. and Rudel, R. and Raubal, M.},
   number = {9},
   pages = {2674},
   year = {2019},
   doi = {10.3390/su11092674},
   url = {}
}
Download
Colic, N., Rinaldi, F. (2019). Improving spaCy dependency annotation and PoS tagging web service using independent NER services. Genomics Inform 17(2), e21.

Improving spaCy dependency annotation and PoS tagging web service using independent NER services

@ARTICLE{rinaldi2019c,
   title = {Improving {spaCy} dependency annotation and {PoS} tagging web service using independent {NER} services},
   journal = {Genomics Inform},
   volume = {17},
   author = {Colic, N. and Rinaldi, F.},
   number = {2},
   pages = {e21},
   year = {2019},
   doi = {10.5808/GI.2019.17.2.e21},
   url = {}
}
Download
Correia, A.H.C., de Campos, C.P., van der Gaag, L.C. (2019). An experimental study of prior dependence in Bayesian network structure learning. In De Bock, J., de Campos, C.P., de Cooman, G., Quaeghebeur, E., Wheeler, G. (Eds), Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications (ISIPTA '19), PMLR 103, JMLR.org, pp. 78–81.

An experimental study of prior dependence in Bayesian network structure learning

@INPROCEEDINGS{Linda2910d,
   title = {An experimental study of prior dependence in {B}ayesian network structure learning},
   editor = {De Bock, J. and de Campos, C.P. and de Cooman, G. and Quaeghebeur, E. and Wheeler, G.},
   publisher = {JMLR.org},
   series = {PMLR},
   volume = {103},
   booktitle = {Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications ({ISIPTA} '19)},
   author = {Correia, A.H.C. and de Campos, C.P. and van der Gaag, L.C.},
   pages = {78--81},
   year = {2019},
   doi = {},
   url = {https://proceedings.mlr.press/v103/correia19a.html}
}
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Ellendorff, T., Furrer, L., Colic, N., Aepli, N., Rinaldi, F. (2019). Approaching SMM4H with merged models and multi-task learning. In Proceedings of the Fourth Social Media Mining for Health Applications (#smm4h) Workshop & Shared Task, Association for Computational Linguistics, pp. 58–61.

Approaching SMM4H with merged models and multi-task learning

@INPROCEEDINGS{rinaldi2019g,
   title = {Approaching {SMM4H} with merged models and multi-task learning},
   publisher = {Association for Computational Linguistics},
   booktitle = {Proceedings of the Fourth Social Media Mining for Health Applications (\#smm4h) Workshop & Shared Task},
   author = {Ellendorff, T. and Furrer, L. and Colic, N. and Aepli, N. and Rinaldi, F.},
   pages = {58--61},
   year = {2019},
   doi = {10.18653/v1/W19-3208},
   url = {https://www.aclweb.org/anthology/W19-3208}
}
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Furrer, L., Cornelius, J., Rinaldi, F. (2019). UZH@CRAFT-ST: a sequence-labeling approach to concept recognition. In Proceedings of the 5th Workshop on Bionlp Open Shared Tasks, Association for Computational Linguistics, pp. 185–195.

UZH@CRAFT-ST: a sequence-labeling approach to concept recognition

@INPROCEEDINGS{rinaldi2019h,
   title = {{UZH@CRAFT}-{ST}: a sequence-labeling approach to concept recognition},
   publisher = {Association for Computational Linguistics},
   booktitle = {Proceedings of the 5th Workshop on Bionlp Open Shared Tasks},
   author = {Furrer, L. and Cornelius, J. and Rinaldi, F.},
   pages = {185--195},
   year = {2019},
   doi = {10.18653/v1/D19-5726},
   url = {}
}
Download
Furrer, L., Jancso, A., Colic, N., Rinaldi, F. (2019). Oger++: hybrid multi-type entity recognition. Journal of Cheminformatics 11(1), 7.

Oger++: hybrid multi-type entity recognition

@ARTICLE{rinaldi2019d,
   title = {Oger++: hybrid multi-type entity recognition},
   journal = {Journal of Cheminformatics},
   publisher = {BioMed Central},
   volume = {11},
   author = {Furrer, L. and Jancso, A. and Colic, N. and Rinaldi, F.},
   number = {1},
   pages = {7},
   year = {2019},
   doi = {10.1186/s13321-018-0326-3},
   url = {https://doi.org/10.5167/uzh-162875}
}
Download
Kanjirangat, V., Antonucci, A. (2019). NOVEL2GRAPH: Visual summaries of narrative text enhanced by machine learning. Proceedings of the Text2StoryIR'19 Workshop, Cologne, Germany, 14-April-2019, pp. 29–37.

NOVEL2GRAPH: Visual summaries of narrative text enhanced by machine learning

@ARTICLE{vani2019a,
   title = {{NOVEL2GRAPH}: {V}isual summaries of narrative text enhanced by machine learning},
   journal = {Proceedings of the {Text2StoryIR'19} Workshop, Cologne, Germany, 14-April-2019},
   editor = {A. Jorge, R. Campos, A. Jatowt, S. Bhatia},
   publisher = {ceur},
   author = {Kanjirangat, V. and Antonucci, A.},
   pages = {29--37},
   year = {2019},
   doi = {},
   url = {http://ceur-ws.org/Vol-2342/paper4.pdf}
}
Download
Kanjirangat, V., Oita, M., Oezdemir-Zaech, F. (2019). Semantically corroborating neural attention for biomedical question answering. In Machine Learning and Knowledge Discovery in Databases, Springer, Lecture Notes in Computer Science, pp. 670–685.

Semantically corroborating neural attention for biomedical question answering

@INPROCEEDINGS{supsi2019d,
   title = {Semantically corroborating neural attention for biomedical question answering},
   publisher = {Springer, Lecture Notes in Computer Science},
   booktitle = {Machine Learning and Knowledge Discovery in Databases},
   author = {Kanjirangat, V. and Oita, M. and Oezdemir-Zaech, F.},
   pages = {670--685},
   year = {2019},
   doi = {10.1007/978-3-030-43887-6_60},
   url = {}
}
Download
Kim, J.D., Cohen, K.B., Collier, N., Lu, Z., Rinaldi, F. (2019). Introduction to BLAH5 special issue: recent progress on interoperability of biomedical text mining. Genomics Inform 17(2), e12.

Introduction to BLAH5 special issue: recent progress on interoperability of biomedical text mining

@ARTICLE{rinaldi2019b,
   title = {Introduction to {BLAH5} special issue: recent progress on interoperability of biomedical text mining},
   journal = {Genomics Inform},
   volume = {17},
   author = {Kim, J.D. and Cohen, K.B. and Collier, N. and Lu, Z. and Rinaldi, F.},
   number = {2},
   pages = {e12},
   year = {2019},
   doi = {10.5808/GI.2019.17.2.e12},
   url = {}
}
Download
Mattei, L., Soares, D.L., Antonucci, A., Mauà, D.D., Facchini, A. (2019). Exploring the space of probabilistic sentential decision diagrams. In Proceedings of the 3rd Tractable Probabilistic Modeling Workshop, 36th International Conference on Machine Learning.

Exploring the space of probabilistic sentential decision diagrams

@INPROCEEDINGS{supsi2019a,
   title = {Exploring the space of probabilistic sentential decision diagrams},
   booktitle = {Proceedings of the 3rd Tractable Probabilistic Modeling Workshop, 36th International Conference on Machine Learning},
   author = {Mattei, L. and Soares, D.L. and Antonucci, A. and Mau\`a, D.D. and Facchini, A.},
   year = {2019},
   doi = {},
   url = {https://drive.google.com/file/d/1PkckPpeLUOP_Oeik_q4MprD6ZJeekqHZ/view}
}
Download
Mauri, A., Lettori, J., Fusi, G., Fausti, D., Mor, M., Braghin, F., Legnani, G., Roveda, L. (2019). Mechanical and control design of an industrial exoskeleton for advanced human empowering in heavy parts manipulation tasks. MDPI Robotics.

Mechanical and control design of an industrial exoskeleton for advanced human empowering in heavy parts manipulation tasks

@ARTICLE{Roveda2019b,
   title = {Mechanical and control design of an industrial exoskeleton for advanced human empowering in heavy parts manipulation tasks},
   journal = {{MDPI} Robotics},
   author = {Mauri, A. and Lettori, J. and Fusi, G. and Fausti, D. and Mor, M. and Braghin, F. and Legnani, G. and Roveda, L.},
   year = {2019},
   doi = {10.3390/robotics8030065},
   url = {}
}
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Mejari, M., Petreczky, M. (2019). Realization and identification algorithm for stochastic lpv state-space models with exogenous inputs.. IFAC-PapersOnLine 52(28), pp. 13–19.

Realization and identification algorithm for stochastic lpv state-space models with exogenous inputs.

@ARTICLE{mejari2019a,
   title = {Realization and identification algorithm for stochastic lpv state-space models with exogenous inputs.},
   journal = {{IFAC}-{PapersOnLine}},
   volume = {52},
   author = {Mejari, M. and Petreczky, M.},
   number = {28},
   pages = {13--19},
   year = {2019},
   doi = {https://doi.org/10.1016/j.ifacol.2019.12.340},
   url = {https://www.sciencedirect.com/science/article/pii/S2405896319322402}
}
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Mejari, M., Petreczky, M. (2019). Consistent and computationally efficient estimation for stochastic lpv state-space models: realization based approach. In 2019 Ieee 58th Conference on Decision and Control (cdc), pp. 3805–3810.

Consistent and computationally efficient estimation for stochastic lpv state-space models: realization based approach

@INPROCEEDINGS{mejari2019b,
   title = {Consistent and computationally efficient estimation for stochastic lpv state-space models: realization based approach},
   booktitle = {2019 Ieee 58th Conference on Decision and Control ({c}dc)},
   author = {Mejari, M. and Petreczky, M.},
   pages = {3805--3810},
   year = {2019},
   doi = {10.1109/CDC40024.2019.9030164},
   url = {}
}
Download
Mejari, M., Piga, D., Toth, R., Bemporad, A. (2019). Kernelized identification of linear parameter-varying models with linear fractional representation. In 2019 European Control Conference (ecc), Naples, Italy.

Kernelized identification of linear parameter-varying models with linear fractional representation

@INPROCEEDINGS{piga2019e,
   title = {Kernelized identification of linear parameter-varying models with linear fractional representation},
   address = {Naples, Italy},
   booktitle = {2019 European Control Conference ({e}cc)},
   author = {Mejari, M. and Piga, D. and Toth, R. and Bemporad, A.},
   year = {2019},
   doi = {10.23919/ECC.2019.8796150},
   url = {}
}
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Miranda, E., Zaffalon, M. (2019). Compatibility, coherence and the RIP. In Destercke, S.,Denoeux, T., Gil, M. A., Grzegorzewski, P., Hryniewicz, O. (Ed), Uncertainty Modelling in Data Science, Advances in Intelligent Systems and Computing 832, Springer, pp. 166–174.

Compatibility, coherence and the RIP

@INCOLLECTION{zaffalon2018a,
   title = {Compatibility, coherence and the {RIP}},
   editor = {Destercke, S.,Denoeux, T., Gil, M. A., Grzegorzewski, P., Hryniewicz, O.},
   publisher = {Springer},
   series = {Advances in Intelligent Systems and Computing},
   volume = {832},
   booktitle = {Uncertainty Modelling in Data Science},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {166--174},
   year = {2019},
   doi = {10.1007/978-3-319-97547-4_22},
   url = {}
}
Download
Musumeci, F., Rottondi, C.E.M., Corani, G., Shahkarami, S., Cugini, F., Tornatore, M. (2019). A tutorial on machine learning for failure management in optical networks. Journal of Lightwave Technology 37(16), pp. 4125–4139.

A tutorial on machine learning for failure management in optical networks

@ARTICLE{corani2019b,
   title = {A tutorial on machine learning for failure management in optical networks},
   journal = {Journal of Lightwave Technology},
   volume = {37},
   author = {Musumeci, F. and Rottondi, C.E.M. and Corani, G. and Shahkarami, S. and Cugini, F. and Tornatore, M.},
   number = {16},
   pages = {4125--4139},
   year = {2019},
   doi = {10.1109/JLT.2019.2922586},
   url = {}
}
Download
Oita, M. (2019). Reverse engineering creativity into interpretable neural networks. In Future of Information and Communications, Lecture Notes in Networks and Systems 70, pp. 235–247.

Reverse engineering creativity into interpretable neural networks

@INPROCEEDINGS{oita2019innGenuity,
   title = {Reverse engineering creativity into interpretable neural networks},
   series = {Lecture Notes in Networks and Systems},
   volume = {70},
   booktitle = {Future of Information and Communications},
   author = {Oita, M.},
   pages = {235--247},
   year = {2019},
   doi = {10.1007/978-3-030-12385-7_19},
   url = {}
}
Download
Oita, M. (2019). Incremental alignment of metaphoric language model for poetry composition. In Intelligent Computing, Springer, "Advances in Intelligent Systems and Computing", pp. 834–845.

Incremental alignment of metaphoric language model for poetry composition

@INPROCEEDINGS{oita2019poetryComposition,
   title = {Incremental alignment of metaphoric language model for poetry composition},
   publisher = {Springer, "Advances in Intelligent Systems and Computing"},
   booktitle = {Intelligent Computing},
   author = {Oita, M.},
   pages = {834--845},
   year = {2019},
   doi = {10.1007/978-3-030-22871-2_59},
   url = {}
}
Download
Piga, D. (2019). Finite-horizon integration for continuous-time identification: bias analysis and application to variable stiffness actuators. International Journal of Control 93(10), pp. 2378–2391.

Finite-horizon integration for continuous-time identification: bias analysis and application to variable stiffness actuators

@ARTICLE{piga2019c,
   title = {Finite-horizon integration for continuous-time identification: bias analysis and application to variable stiffness actuators},
   journal = {International Journal of Control},
   publisher = {Taylor & Francis},
   volume = {93},
   author = {Piga, D.},
   number = {10},
   pages = {2378--2391},
   year = {2019},
   doi = {10.1080/00207179.2018.1557348},
   url = {}
}
Download
Piga, D., Benavoli, A. (2019). Semialgebraic outer approximations for set-valued nonlinear filtering. In 2019 European Control Conference (ECC), Naples, Italy.

Semialgebraic outer approximations for set-valued nonlinear filtering

@INPROCEEDINGS{piga2019f,
   title = {Semialgebraic outer approximations for set-valued nonlinear filtering},
   address = {Naples, Italy},
   booktitle = {2019 European Control Conference ({ECC})},
   author = {Piga, D. and Benavoli, A.},
   year = {2019},
   doi = {10.23919/ECC.2019.8795731},
   url = {}
}
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Piga, D., Forgione, M., Formentin, S., Bemporad, A. (2019). Performance-oriented model learning for data-driven MPC design. IEEE Control Systems Letters 3(3), pp. 577–582.

Performance-oriented model learning for data-driven MPC design

@ARTICLE{piga2019a,
   title = {Performance-oriented model learning for data-driven {MPC} design},
   journal = {{IEEE} Control Systems Letters},
   volume = {3},
   author = {Piga, D. and Forgione, M. and Formentin, S. and Bemporad, A.},
   number = {3},
   pages = {577--582},
   year = {2019},
   doi = {10.1109/LCSYS.2019.2913347},
   url = {}
}
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Renooij, S., van der Gaag, L.C. (2019). The hidden elegance of causal interaction models. In Ben Amor, N., Quost, B., Theobald, M (Eds), 13th International Conference on Scalable Uncertainty Management (SUM '19), Lecture Notes in Artificial Intelligence 11940, Springer, pp. 38–51.

The hidden elegance of causal interaction models

@INPROCEEDINGS{linda2019a,
   title = {The hidden elegance of causal interaction models},
   editor = {Ben Amor, N. and Quost, B. and Theobald, M},
   publisher = {Springer},
   series = {Lecture Notes in Artificial Intelligence},
   volume = {11940},
   booktitle = {13th International Conference on Scalable Uncertainty Management ({SUM} '19)},
   author = {Renooij, S. and van der Gaag, L.C.},
   pages = {38--51},
   year = {2019},
   doi = {10.1007/978-3-030-35514-2_4},
   url = {}
}
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Renooij, S., van der Gaag, L.C., Leray, Ph. (2019). On intercausal interactions in probabilistic relational models. In De Bock, J., de Campos, C.P., de Cooman, G., Quaeghebeur, E., Wheeler, G. (Eds), Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications (ISIPTA '19), Proceedings of Machine Learning Research 103, pp. 327–329.

On intercausal interactions in probabilistic relational models

@INPROCEEDINGS{Linda2019b,
   title = {On intercausal interactions in probabilistic relational models},
   editor = {De Bock, J. and de Campos, C.P. and de Cooman, G. and Quaeghebeur, E. and Wheeler, G.},
   series = {Proceedings of Machine Learning Research},
   volume = {103},
   booktitle = {Proceedings of the Eleventh International Symposium on Imprecise Probabilities: Theories and Applications ({ISIPTA} '19)},
   author = {Renooij, S. and van der Gaag, L.C. and Leray, Ph.},
   pages = {327--329},
   year = {2019},
   doi = {},
   url = {https://proceedings.mlr.press/v103/renooij19a.html}
}
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Rodriguez-Esteban, R., Vishnyakova, D., Rinaldi, F. (2019). Revisiting the decay of scientific email addresses. bioRxiv.

Revisiting the decay of scientific email addresses

@ARTICLE{rinaldi2019j,
   title = {Revisiting the decay of scientific email addresses},
   journal = {{bioRxiv}},
   publisher = {Cold Spring Harbor Laboratory},
   author = {Rodriguez-Esteban, R. and Vishnyakova, D. and Rinaldi, F.},
   year = {2019},
   doi = {10.1101/633255},
   url = {https://www.biorxiv.org/content/early/2019/05/12/633255}
}
Download
Roveda, L., Haghshenas, S., Caimmi, M., Pedrocchi, N., Molinari Tosatti, L. (2019). Assisting operators in heavy industrial tasks: on the design of an optimized cooperative impedance fuzzy-controller with embedded safety rules. Frontiers in Robotics and AI 6, 75.

Assisting operators in heavy industrial tasks: on the design of an optimized cooperative impedance fuzzy-controller with embedded safety rules

@ARTICLE{Roveda2019a,
   title = {Assisting operators in heavy industrial tasks: on the design of an optimized cooperative impedance fuzzy-controller with embedded safety rules},
   journal = {Frontiers in Robotics and {AI}},
   volume = {6},
   author = {Roveda, L. and Haghshenas, S. and Caimmi, M. and Pedrocchi, N. and Molinari Tosatti, L.},
   pages = {75},
   year = {2019},
   doi = {10.3389/frobt.2019.00075},
   url = {}
}
Download
Salani, M., Corbellini, G., Corani, G. (2019). Hybrid heuristic for the optimal design of photovoltaic installations considering mismatch loss effects. Computers & Operations Research 108, pp. 112–120.

Hybrid heuristic for the optimal design of photovoltaic installations considering mismatch loss effects

@ARTICLE{corani2019a,
   title = {Hybrid heuristic for the optimal design of photovoltaic installations considering mismatch loss effects},
   journal = {Computers & Operations Research},
   volume = {108},
   author = {Salani, M. and Corbellini, G. and Corani, G.},
   pages = {112--120},
   year = {2019},
   doi = {10.1016/j.cor.2019.04.009},
   url = {}
}
Download
Sechidis, K., Azzimonti, L., Pocock, A., Corani, G., Weatherall, J., Brown, G. (2019). Efficient feature selection using shrinkage estimators. Machine Learning 108(8), pp. 1261–1286.

Efficient feature selection using shrinkage estimators

@ARTICLE{azzimonti2019b,
   title = {Efficient feature selection using shrinkage estimators},
   journal = {Machine Learning},
   volume = {108},
   author = {Sechidis, K. and Azzimonti, L. and Pocock, A. and Corani, G. and Weatherall, J. and Brown, G.},
   number = {8},
   pages = {1261--1286},
   year = {2019},
   doi = {10.1007/s10994-019-05795-1},
   url = {}
}
Download
Sheikhalishahi, S., Miotto, R., Dudley, J.T., Lavelli, A., Rinaldi, F., Osmani, V. (2019). Natural language processing of clinical notes on chronic diseases: systematic review. JMIR Med Inform 7(2), e12239.

Natural language processing of clinical notes on chronic diseases: systematic review

@ARTICLE{rinaldi2019f,
   title = {Natural language processing of clinical notes on chronic diseases: systematic review},
   journal = {{JMIR} Med Inform},
   volume = {7},
   author = {Sheikhalishahi, S. and Miotto, R. and Dudley, J.T. and Lavelli, A. and Rinaldi, F. and Osmani, V.},
   number = {2},
   pages = {e12239},
   year = {2019},
   doi = {10.2196/12239},
   url = {http://medinform.jmir.org/2019/2/e12239/}
}
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Vishnyakova, D., Rodriguez-Esteban, R., Rinaldi, F. (2019). A new approach and gold standard toward author disambiguation in MEDLINE. J Am Med Inform Assoc 26(10), pp. 1037–1045.

A new approach and gold standard toward author disambiguation in MEDLINE

@ARTICLE{rinaldi2019a,
   title = {A new approach and gold standard toward author disambiguation in {MEDLINE}},
   journal = {J Am Med Inform Assoc},
   volume = {26},
   author = {Vishnyakova, D. and Rodriguez-Esteban, R. and Rinaldi, F.},
   number = {10},
   pages = {1037--1045},
   year = {2019},
   doi = {10.1093/jamia/ocz028},
   url = {}
}
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top

2018

Antonucci, A., Facchini, A. (2018). A credal extension of independent choice logic. In Proceedings of the 12th International Conference on Scalable Uncertainty Management (SUM 2018), pp. 35–49.

A credal extension of independent choice logic

@INPROCEEDINGS{antonucci2018c,
   title = {A credal extension of independent choice logic},
   booktitle = {Proceedings of the 12th International Conference on Scalable Uncertainty Management ({SUM} 2018)},
   author = {Antonucci, A. and Facchini, A.},
   pages = {35--49},
   year = {2018},
   doi = {10.1007/978-3-030-00461-3_3},
   url = {https://arxiv.org/abs/1806.08298}
}
Download
Antonucci, A., Facchini, A. (2018). Set-valued probabilistic sentential decision diagrams. In Proceedings of the 5th Workshop on Probabilistic Logic Programming, pp. 3–8.

Set-valued probabilistic sentential decision diagrams

@INPROCEEDINGS{antonucci2018d,
   title = {Set-valued probabilistic sentential decision diagrams},
   booktitle = {Proceedings of the 5th Workshop on Probabilistic Logic Programming},
   author = {Antonucci, A. and Facchini, A.},
   pages = {3--8},
   year = {2018},
   doi = {},
   url = {https://ceur-ws.org/Vol-2219/}
}
Download
Bemporad, A., Breschi, V., Piga, D., Boyd, S. (2018). Fitting jump models. Automatica 96, pp. 11–21.

Fitting jump models

@ARTICLE{piga2018e,
   title = {Fitting jump models},
   journal = {Automatica},
   volume = {96},
   author = {Bemporad, A. and Breschi, V. and Piga, D. and Boyd, S.},
   pages = {11--21},
   year = {2018},
   doi = {10.1016/j.automatica.2018.06.022},
   url = {}
}
Download
Breschi, V., Bemporad, A., Piga, D., Boyd, S. (2018). Prediction error methods in learning jump ARMAX models. In 2018 IEEE Conference on Decision and Control (cdc), pp. 2247–2252.

Prediction error methods in learning jump ARMAX models

@INPROCEEDINGS{piga2018i,
   title = {Prediction error methods in learning jump {ARMAX} models},
   booktitle = {2018 {IEEE} Conference on Decision and Control ({c}dc)},
   author = {Breschi, V. and Bemporad, A. and Piga, D. and Boyd, S.},
   pages = {2247--2252},
   year = {2018},
   doi = {10.1109/CDC.2018.8619819},
   url = {}
}
Download
Breschi, V., Piga, D., Bemporad, A. (2018). Kalman filtering for energy disaggregation. In Proc. of the 1st IFAC Workshop on Integrated Assessment Modelling for Environmental Systems 51(5), pp. 108–113.

Kalman filtering for energy disaggregation

@INPROCEEDINGS{piga2018b,
   title = {Kalman filtering for energy disaggregation},
   journal = {{IFAC}-{PapersOnLine}},
   volume = {51},
   booktitle = {Proc. {o}f the 1st {IFAC} Workshop on Integrated Assessment Modelling for Environmental Systems},
   author = {Breschi, V. and Piga, D. and Bemporad, A.},
   number = {5},
   pages = {108--113},
   year = {2018},
   doi = {10.1016/j.ifacol.2018.06.219},
   url = {}
}
Download
Breschi, V., Piga, D., Bemporad, A. (2018). Jump model learning and filtering for energy end-use disaggregation. In Proc. of the 18th IFAC Symposium on System Identification 51(15), pp. 275–280.

Jump model learning and filtering for energy end-use disaggregation

@INPROCEEDINGS{piga2018f,
   title = {Jump model learning and filtering for energy end-use disaggregation},
   volume = {51},
   booktitle = {Proc. {o}f the 18th {IFAC} Symposium on System Identification},
   author = {Breschi, V. and Piga, D. and Bemporad, A.},
   number = {15},
   pages = {275--280},
   year = {2018},
   doi = {10.1016/j.ifacol.2018.09.147},
   url = {}
}
Download
de Campos, C.P., Scanagatta, M., Corani, G., Zaffalon, M. (2018). Entropy-based pruning for learning Bayesian networks using BIC. Artificial Intelligence 260, pp. 42–50.

Entropy-based pruning for learning Bayesian networks using BIC

@ARTICLE{deCampos2018a,
   title = {Entropy-based pruning for learning {B}ayesian networks using {BIC}},
   journal = {Artificial Intelligence},
   volume = {260},
   author = {de Campos, C.P. and Scanagatta, M. and Corani, G. and Zaffalon, M.},
   pages = {42--50},
   year = {2018},
   doi = {10.1016/j.artint.2018.04.002},
   url = {}
}
Download
Giusti, A., Huber, D., Gambardella, L.M. (2018). Introducing Machine Learning Concepts by Training a Neural Network to Recognize Hand Gestures. In Proc. of AAAI Symposium On Educational Advances In Artificial Intelligence 32(1).

Introducing Machine Learning Concepts by Training a Neural Network to Recognize Hand Gestures

@INPROCEEDINGS{huber2018a,
   title = {Introducing {M}achine {L}earning {C}oncepts by {T}raining a {N}eural {N}etwork to {R}ecognize {H}and {G}estures},
   journal = {Proceedings of the {AAAI} Conference on Artificial Intelligence},
   volume = {32},
   booktitle = {Proc. {o}f {AAAI} Symposium On Educational Advances In Artificial Intelligence},
   author = {Giusti, A. and Huber, D. and Gambardella, L.M.},
   number = {1},
   year = {2018},
   doi = {10.1609/aaai.v32i1.11400},
   url = {}
}
Download
Kern, H., Corani, G., Huber, D., Vermes, N., Zaffalon, M. (2018). What interplay of factors influences the place of death in cancer patients? an innovative probabilistic approach sheds light on a well-known question. Journal of Pain and Symptom Management 56(6), e25.

What interplay of factors influences the place of death in cancer patients? an innovative probabilistic approach sheds light on a well-known question

@ARTICLE{kern2018a,
   title = {What interplay of factors influences the place of death in cancer patients? {a}n innovative probabilistic approach sheds light on a well-known question},
   journal = {Journal of Pain and Symptom Management},
   publisher = {Elsevier},
   volume = {56},
   booktitle = {Journal of Pain and Symptom Management},
   author = {Kern, H. and Corani, G. and Huber, D. and Vermes, N. and Zaffalon, M.},
   number = {6},
   pages = {e25},
   year = {2018},
   doi = {10.1016/j.jpainsymman.2018.10.016},
   url = {}
}
Download
Marchetti, S., Antonucci, A. (2018). Reliable uncertain evidence modeling in Bayesian networks by credal networks. In Proceedings of the 31st International Flairs Conference (FLAIRS-31), AAAI Press, pp. 513–518.

Reliable uncertain evidence modeling in Bayesian networks by credal networks

@INPROCEEDINGS{antonucci2018a,
   title = {Reliable uncertain evidence modeling in {B}ayesian networks by credal networks},
   publisher = {AAAI Press},
   booktitle = {Proceedings of the 31st International Flairs Conference ({FLAIRS}-31)},
   author = {Marchetti, S. and Antonucci, A.},
   pages = {513--518},
   year = {2018},
   doi = {},
   url = {}
}
Download
Marchetti, S., Antonucci, A. (2018). Imaginary kinematics. In Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence, AUAI Press, pp. 104–113.

Imaginary kinematics

@INPROCEEDINGS{antonucci2018b,
   title = {Imaginary kinematics},
   publisher = {AUAI Press},
   booktitle = {Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence},
   author = {Marchetti, S. and Antonucci, A.},
   pages = {104--113},
   year = {2018},
   doi = {},
   url = {https://www.auai.org/uai2018/accepted.php#top}
}
Download
Mejari, M., Naik, V.V., Piga, D., Bemporad, A. (2018). Regularized moving-horizon PWA regression for LPV system identification. In Proc. of the 18th IFAC Symposium on System Identification 51(15), pp. 1092–1097.

Regularized moving-horizon PWA regression for LPV system identification

@INPROCEEDINGS{piga2018d,
   title = {Regularized moving-horizon {PWA} regression for {LPV} system identification},
   volume = {51},
   booktitle = {Proc. {o}f the 18th {IFAC} Symposium on System Identification},
   author = {Mejari, M. and Naik, V.V. and Piga, D. and Bemporad, A.},
   number = {15},
   pages = {1092--1097},
   year = {2018},
   doi = {10.1016/j.ifacol.2018.09.048},
   url = {}
}
Download
Mejari, M., Naik, V.V., Piga, D., Bemporad, A. (2018). Energy disaggregation using piecewise affine regression and binary quadratic programming. In 2018 IEEE Conference on Decision and Control (cdc), pp. 3116–3121.

Energy disaggregation using piecewise affine regression and binary quadratic programming

@INPROCEEDINGS{piga2018h,
   title = {Energy disaggregation using piecewise affine regression and binary quadratic programming},
   booktitle = {2018 {IEEE} Conference on Decision and Control ({c}dc)},
   author = {Mejari, M. and Naik, V.V. and Piga, D. and Bemporad, A.},
   pages = {3116--3121},
   year = {2018},
   doi = {10.1109/CDC.2018.8619175},
   url = {}
}
Download
Mejari, M., Piga, D., Bemporad, A. (2018). A bias-correction method for closed-loop identification of linear parameter-varying systems. Automatica 87, pp. 128–141.

A bias-correction method for closed-loop identification of linear parameter-varying systems

@ARTICLE{piga2018c,
   title = {A bias-correction method for closed-loop identification of linear parameter-varying systems},
   journal = {Automatica},
   volume = {87},
   author = {Mejari, M. and Piga, D. and Bemporad, A.},
   pages = {128--141},
   year = {2018},
   doi = {10.1016/j.automatica.2017.09.014},
   url = {}
}
Download
Piga, D., Formentin, S., Bemporad, A. (2018). Direct data-driven control of constrained systems. IEEE Transactions on Control Systems Technology 26(4), pp. 1422–1429.

Direct data-driven control of constrained systems

@ARTICLE{piga2018a,
   title = {Direct data-driven control of constrained systems},
   journal = {{IEEE} Transactions on Control Systems Technology},
   volume = {26},
   author = {Piga, D. and Formentin, S. and Bemporad, A.},
   number = {4},
   pages = {1422--1429},
   year = {2018},
   doi = {10.1109/TCST.2017.2702118},
   url = {}
}
Download
Scanagatta, M., Corani, G., de Campos, C.P., Zaffalon, M. (2018). Approximate structure learning for large Bayesian networks. Machine Learning 107(8-10), pp. 1209–1227.

Approximate structure learning for large Bayesian networks

@ARTICLE{scanagatta2018b,
   title = {Approximate structure learning for large {B}ayesian networks},
   journal = {Machine Learning},
   publisher = {Springer},
   volume = {107},
   author = {Scanagatta, M. and Corani, G. and de Campos, C.P. and Zaffalon, M.},
   number = {8-10},
   pages = {1209--1227},
   year = {2018},
   doi = {10.1007/s10994-018-5701-9},
   url = {}
}
Download
Scanagatta, M., Corani, G., Zaffalon, M., Yoo, J., Kang, U. (2018). Efficient learning of bounded-treewidth Bayesian networks from complete and incomplete data sets. International Journal of Approximate Reasoning 95, pp. 152–166.

Efficient learning of bounded-treewidth Bayesian networks from complete and incomplete data sets

@ARTICLE{scanagatta2018a,
   title = {Efficient learning of bounded-treewidth {B}ayesian networks from complete and incomplete data sets},
   journal = {International Journal of Approximate Reasoning},
   volume = {95},
   author = {Scanagatta, M. and Corani, G. and Zaffalon, M. and Yoo, J. and Kang, U.},
   pages = {152--166},
   year = {2018},
   doi = {10.1016/j.ijar.2018.02.004},
   url = {}
}
Download
Selvi, D., Piga, D., Bemporad, A. (2018). Towards direct data-driven model-free design of optimal controllers. In 2018 European Control Conference (ecc), pp. 2836–2841.

Towards direct data-driven model-free design of optimal controllers

@INPROCEEDINGS{piga2018g,
   title = {Towards direct data-driven model-free design of optimal controllers},
   booktitle = {2018 European Control Conference ({e}cc)},
   author = {Selvi, D. and Piga, D. and Bemporad, A.},
   pages = {2836--2841},
   year = {2018},
   doi = {10.23919/ECC.2018.8550184},
   url = {}
}
Download
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2017

Arnone, E., Azzimonti, L., Nobile, F., Sangalli, L.M. (2017). A time-dependent PDE regularization to model functional data defined over spatio-temporal domains. In Aneiros G., Bongiorno E.G., Cao R., Vieu P. (Ed), Functional Statistics and Related Fields, Springer International Publishing, pp. 41–44.

A time-dependent PDE regularization to model functional data defined over spatio-temporal domains

@INBOOK{azzimonti2017b,
   title = {A time-dependent {PDE} regularization to model functional data defined over spatio-temporal domains},
   editor = {Aneiros G., Bongiorno E.G., Cao R., Vieu P. },
   publisher = {Springer International Publishing},
   booktitle = {Functional Statistics and Related Fields},
   author = {Arnone, E. and Azzimonti, L. and Nobile, F. and Sangalli, L.M.},
   pages = {41--44},
   year = {2017},
   doi = {10.1007/978-3-319-55846-2_6},
   url = {}
}
Download
Azzimonti, L., Corani, G., Zaffalon, M. (2017). Hierarchical Multinomial-Dirichlet model for the estimation of conditional probability tables. In Raghavan, V., Aluru, S., Karypis, G., Miele, L., Wu, X. (Ed), 2017 IEEE 17th International Conference on Data Mining (ICDM), pp. 739–744.

Hierarchical Multinomial-Dirichlet model for the estimation of conditional probability tables

@INPROCEEDINGS{azzimonti2017c,
   title = {Hierarchical {M}ultinomial-{D}irichlet model for the estimation of conditional probability tables},
   editor = {Raghavan, V., Aluru, S., Karypis, G., Miele, L., Wu, X.},
   booktitle = {2017 {IEEE} 17th International Conference on Data Mining ({ICDM})},
   author = {Azzimonti, L. and Corani, G. and Zaffalon, M.},
   pages = {739--744},
   year = {2017},
   doi = {10.1109/ICDM.2017.85},
   url = {}
}
Download
Balleri, A., Farina, A., Benavoli, A. (2017). Coordination of optimal guidance law and adaptive radiated waveform for interception and rendezvous problems. IET Radar, Sonar & Navigation 11(7), pp. 1132–139.

Coordination of optimal guidance law and adaptive radiated waveform for interception and rendezvous problems

@ARTICLE{benavoli2017a,
   title = {Coordination of optimal guidance law and adaptive radiated waveform for interception and rendezvous problems},
   journal = {{IET} Radar, Sonar & Navigation},
   publisher = {Institution of Engineering and Technology},
   volume = {11},
   author = {Balleri, A. and Farina, A. and Benavoli, A.},
   number = {7},
   pages = {1132--139},
   year = {2017},
   doi = {10.1049/iet-rsn.2016.0547},
   url = {}
}
Download
Benavoli, A., Corani, G., Demsar, J., Zaffalon, M. (2017). Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis. Journal of Machine Learning Research 18(77), pp. 1–36.

Time for a change: a tutorial for comparing multiple classifiers through Bayesian analysis

@ARTICLE{benavoli2016e,
   title = {Time for a change: a tutorial for comparing multiple classifiers through {B}ayesian analysis},
   journal = {Journal of Machine Learning Research},
   volume = {18},
   author = {Benavoli, A. and Corani, G. and Demsar, J. and Zaffalon, M.},
   number = {77},
   pages = {1--36},
   year = {2017},
   doi = {},
   url = {http://jmlr.org/papers/v18/16-305.html}
}
Download
Benavoli, A., Facchini, A., Vicente-Perez, J., Zaffalon, M. (2017). A polarity theory for sets of desirable gambles. In Proc. ISIPTA '17 Int. Symposium on Imprecise Probability: Theories and Applications 62, PMLR, pp. 1–12.

A polarity theory for sets of desirable gambles

@INPROCEEDINGS{Benavoli2017c,
   title = {A polarity theory for sets of desirable gambles},
   publisher = {PMLR},
   volume = {62},
   booktitle = {Proc. {ISIPTA} '17 Int. Symposium on Imprecise Probability: Theories and Applications},
   author = {Benavoli, A. and Facchini, A. and Vicente-Perez, J. and Zaffalon, M.},
   pages = {1--12},
   year = {2017},
   doi = {},
   url = {http://proceedings.mlr.press/v62/benavoli17b/benavoli17b.pdf}
}
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Benavoli, A., Facchini, A., Piga, D., Zaffalon, M. (2017). SOS for bounded rationality. In Proceedings of Machine Learning Research 62, PMLR, pp. 25–36.

SOS for bounded rationality

@INPROCEEDINGS{Benavoli2017b,
   title = {{SOS} for bounded rationality},
   publisher = {PMLR},
   volume = {62},
   booktitle = {Proceedings of Machine Learning Research},
   author = {Benavoli, A. and Facchini, A. and Piga, D. and Zaffalon, M.},
   pages = {25--36},
   year = {2017},
   doi = {},
   url = {http://proceedings.mlr.press/v62/benavoli17a/benavoli17a.pdf}
}
Download
Benavoli, A., Facchini, A., Zaffalon, M. (2017). Bayes + Hilbert = Quantum Mechanics. In Proceedings of the 14th Interational Conference on Quantum Physics and Logic (qpl 2017), Nijmegen, the Netherlands, 3-7 July.

Bayes + Hilbert = Quantum Mechanics

@INPROCEEDINGS{Benavoli2017m,
   title = {Bayes + {H}ilbert = {Q}uantum {M}echanics},
   booktitle = {Proceedings of the 14th Interational Conference on Quantum Physics and Logic ({q}pl 2017), Nijmegen, the Netherlands, 3-7 July},
   author = {Benavoli, A. and Facchini, A. and Zaffalon, M.},
   year = {2017},
   doi = {},
   url = {http://qpl.science.ru.nl/papers/QPL_2017_paper_4.pdf}
}
Download
Bucher, D., Mangili, F., Bonesana, C., Jonietz, D., Cellina, F., Raubal, M. (2017). Demo abstract: extracting eco-feedback information from automatic activity tracking to promote energy-efficient individual mobility behavior. In 33(1), pp. 1–2.

Demo abstract: extracting eco-feedback information from automatic activity tracking to promote energy-efficient individual mobility behavior

@INPROCEEDINGS{mangili2017c,
   title = {Demo abstract: extracting eco-feedback information from automatic activity tracking to promote energy-efficient individual mobility behavior},
   journal = {Computer Science - Research and Development},
   volume = {33},
   author = {Bucher, D. and Mangili, F. and Bonesana, C. and Jonietz, D. and Cellina, F. and Raubal, M.},
   number = {1},
   pages = {1--2},
   year = {2017},
   doi = {10.1007/s00450-017-0375-2},
   url = {}
}
Download
Corani, G., Benavoli, A., Demšar, J., Mangili, F., Zaffalon, M. (2017). Statistical comparison of classifiers through Bayesian hierarchical modelling. Machine Learning 106(11), pp. 1817–1837.

Statistical comparison of classifiers through Bayesian hierarchical modelling

@ARTICLE{corani2017a,
   title = {Statistical comparison of classifiers through {B}ayesian hierarchical modelling},
   journal = {Machine Learning},
   volume = {106},
   author = {Corani, G. and Benavoli, A. and Demšar, J. and Mangili, F. and Zaffalon, M.},
   number = {11},
   pages = {1817--1837},
   year = {2017},
   doi = {10.1007/s10994-017-5641-9},
   url = {}
}
Download
Cruder, C., Falla, D., Mangili, F., Azzimonti, L., Araújo, L., Williamon, A., Barbero, M. (2017). Profiling the location and extent of musicians' pain using digital pain drawings. PAIN Practice 18(1), pp. 53–66.

Profiling the location and extent of musicians' pain using digital pain drawings

@ARTICLE{mangili2017a,
   title = {Profiling the location and extent of musicians' pain using digital pain drawings},
   journal = {{PAIN} Practice},
   publisher = {Wiley},
   volume = {18},
   author = {Cruder, C. and Falla, D. and Mangili, F. and Azzimonti, L. and Ara\'ujo, L. and Williamon, A. and Barbero, M.},
   number = {1},
   pages = {53--66},
   year = {2017},
   doi = {10.1111/papr.12581},
   url = {}
}
Download
Gorini, F., Azzimonti, L., Delfanti, G., Scarfò, L., Scielzo, C., Bertilaccio, M.T., Ranghetti, P., Gulino, A., Doglioni, C., Napoli, A.D., Capri, M., Franceschi, C., Calligaris-Cappio, F., Ghia, P., Bellone, M., Dellabona, P., Casorati, G., de Lalla, C. (2017). Invariant NKT cells contribute to Chronic Lymphocytic Leukemia surveillance and prognosis. Blood 129(26), pp. 3440–3451.

Invariant NKT cells contribute to Chronic Lymphocytic Leukemia surveillance and prognosis

@ARTICLE{azzimonti2017a,
   title = {Invariant {NKT} cells contribute to {C}hronic {L}ymphocytic {L}eukemia surveillance and prognosis},
   journal = {Blood},
   volume = {129},
   author = {Gorini, F. and Azzimonti, L. and Delfanti, G. and Scarf\`o, L. and Scielzo, C. and Bertilaccio, M.T. and Ranghetti, P. and Gulino, A. and Doglioni, C. and Napoli, A.D. and Capri, M. and Franceschi, C. and Calligaris-Cappio, F. and Ghia, P. and Bellone, M. and Dellabona, P. and Casorati, G. and de Lalla, C.},
   number = {26},
   pages = {3440--3451},
   year = {2017},
   doi = {10.1182/blood-2016-11-751065},
   url = {}
}
Download
Mangili, F., Bonesana, C., Antonucci, A. (2017). Reliable knowledge-based adaptive tests by credal networks. In Antonucci, A., Cholvy, L., Papini, O. (Eds), Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2017, Lecture Notes in Computer Science 10369, Springer, Cham, pp. 282–291.

Reliable knowledge-based adaptive tests by credal networks

@INPROCEEDINGS{mangili2017b,
   title = {Reliable knowledge-based adaptive tests by credal networks},
   editor = {Antonucci, A. and Cholvy, L. and Papini, O.},
   publisher = {Springer, Cham},
   series = {Lecture Notes in Computer Science},
   volume = {10369},
   booktitle = {Symbolic and Quantitative Approaches to Reasoning {w}ith Uncertainty. {ECSQARU} 2017 },
   author = {Mangili, F. and Bonesana, C. and Antonucci, A.},
   pages = {282--291},
   year = {2017},
   doi = {10.1007/978-3-319-61581-3_26},
   url = {}
}
Download
Piga, D., Benavoli, A. (2017). A unified framework for deterministic and probabilistic d-stability analysis of uncertain polynomial matrices. IEEE Transactions on Automatic Control PP(99).

A unified framework for deterministic and probabilistic d-stability analysis of uncertain polynomial matrices

@ARTICLE{piga2017a,
   title = {A unified framework for deterministic and probabilistic d-stability analysis of uncertain polynomial matrices},
   journal = {{IEEE} Transactions on Automatic Control},
   volume = {PP},
   author = {Piga, D. and Benavoli, A.},
   number = {99},
   year = {2017},
   doi = {10.1109/TAC.2017.2699281},
   url = {}
}
Download
Scanagatta, M., Corani, G., Zaffalon, M. (2017). Improved local search in Bayesian networks structure learning. In Antti Hyttinen, Joe Suzuki, Brandon Malone (Eds), Proceedings of The 3rd International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), Proceedings of Machine Learning Research 73, PMLR, pp. 45–56.

Improved local search in Bayesian networks structure learning

@INPROCEEDINGS{scanagatta2017,
   title = {Improved local search in {B}ayesian networks structure learning},
   editor = {Antti Hyttinen and Joe Suzuki and Brandon Malone},
   publisher = {PMLR},
   series = {Proceedings of Machine Learning Research},
   volume = {73},
   booktitle = {Proceedings of The 3rd International Workshop on Advanced Methodologies for Bayesian Networks ({AMBN})},
   author = {Scanagatta, M. and Corani, G. and Zaffalon, M.},
   pages = {45--56},
   year = {2017},
   doi = {},
   url = {https://proceedings.mlr.press/v73/scanagatta17a.html}
}
Download
Soullard, Y., Antonucci, A., Destercke, S. (2017). Technical gestures recognition by set-valued hidden Markov models with prior knowledge. In Ferraro, M. B., Giordani, P., Vantaggi, B., Gagolewski, M., Gil, M. A., Grzegorzewski, P., Hryniewicz, O. (Eds), Soft Methods for Data Science, Advances in Intelligent Systems and Computing 456, Springer, pp. 455–462.

Technical gestures recognition by set-valued hidden Markov models with prior knowledge

@INCOLLECTION{antonucci2016a,
   title = {Technical gestures recognition by set-valued hidden {M}arkov models with prior knowledge},
   editor = {Ferraro, M. B. and Giordani, P. and Vantaggi, B. and Gagolewski, M. and Gil, M. A. and Grzegorzewski, P. and Hryniewicz, O.},
   publisher = {Springer},
   series = {Advances in Intelligent Systems and Computing},
   volume = {456},
   booktitle = {Soft Methods for Data Science},
   author = {Soullard, Y. and Antonucci, A. and Destercke, S.},
   pages = {455--462},
   year = {2017},
   doi = {10.1007/978-3-319-42972-4_56},
   url = {}
}
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Miranda, E., Zaffalon, M. (2017). Full conglomerability, continuity and marginal extension. In Ferraro, M. B., Giordani, P., Vantaggi, B., Gagolewski, M., Gil, M. A., Grzegorzewski, P., Hryniewicz, O. (Eds), Soft Methods for Data Science, Advances in Intelligent Systems and Computing 456, Springer, pp. 355–362.

Full conglomerability, continuity and marginal extension

@INCOLLECTION{zaffalon2017a,
   title = {Full conglomerability, continuity and marginal extension},
   editor = {Ferraro, M. B. and Giordani, P. and Vantaggi, B. and Gagolewski, M. and Gil, M. A. and Grzegorzewski, P. and Hryniewicz, O.},
   publisher = {Springer},
   series = {Advances in Intelligent Systems and Computing},
   volume = {456},
   booktitle = {Soft Methods for Data Science},
   author = {Miranda, E., Zaffalon, M.},
   pages = {355--362},
   year = {2017},
   doi = {10.1007/978-3-319-42972-4},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2017). Full conglomerability. Journal of Statistical Theory and Practice 11(4), pp. 634–669.

Full conglomerability

@ARTICLE{zaffalon2017b,
   title = {Full conglomerability},
   journal = {Journal of Statistical Theory and Practice},
   volume = {11},
   author = {Miranda, E., Zaffalon, M.},
   number = {4},
   pages = {634--669},
   year = {2017},
   doi = {10.1080/15598608.2017.1295890},
   url = {}
}
Download
Zaffalon, M., Miranda, E. (2017). Axiomatising incomplete preferences through sets of desirable gambles. Journal of Artificial Intelligence Research 60, pp. 1057–1126.

Axiomatising incomplete preferences through sets of desirable gambles

@ARTICLE{zaffalon2017c,
   title = {Axiomatising incomplete preferences through sets of desirable gambles},
   journal = {Journal of Artificial Intelligence Research},
   volume = {60},
   author = {Zaffalon, M. and Miranda, E.},
   pages = {1057--1126},
   year = {2017},
   doi = {10.1613/jair.5230},
   url = {}
}
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2016

Antonucci, A., Corani, G. (2016). The multilabel naive credal classifier. International Journal of Approximate Reasoning 83, pp. 320–336.

The multilabel naive credal classifier

@ARTICLE{antonucci2016c,
   title = {The multilabel naive credal classifier},
   journal = {International Journal of Approximate Reasoning},
   volume = {83},
   author = {Antonucci, A. and Corani, G.},
   pages = {320--336},
   year = {2016},
   doi = {10.1016/j.ijar.2016.10.006},
   url = {}
}
Download
Benavoli, A., de Campos, C.P. (2016). Bayesian dependence tests for continuous, binary and mixed continuous-binary variables. Entropy 18(9), pp. 1–24.

Bayesian dependence tests for continuous, binary and mixed continuous-binary variables

@ARTICLE{benavoli2016g,
   title = {Bayesian dependence tests for continuous, binary and mixed continuous-binary variables},
   journal = {Entropy},
   publisher = {Multidisciplinary Digital Publishing Institute},
   volume = {18},
   author = {Benavoli, A. and de Campos, C.P.},
   number = {9},
   pages = {1--24},
   year = {2016},
   doi = {10.3390/e18090326},
   url = {http://www.mdpi.com/1099-4300/18/9/326}
}
Download
Benavoli, A., Corani, G., Mangili, F. (2016). Should we really use post-hoc tests based on mean-ranks?. Journal of Machine Learning Research 17(5), pp. 1–10.

Should we really use post-hoc tests based on mean-ranks?

@ARTICLE{benavoli2015c,
   title = {Should we really use post-hoc tests based on mean-ranks?},
   journal = {Journal of Machine Learning Research},
   volume = {17},
   author = {Benavoli, A. and Corani, G. and Mangili, F.},
   number = {5},
   pages = {1--10},
   year = {2016},
   doi = {},
   url = {http://jmlr.org/papers/volume17/benavoli16a/benavoli16a.pdf}
}
Download
Benavoli, A., Facchini, A., Zaffalon, M. (2016). Quantum mechanics: the Bayesian theory generalized to the space of hermitian matrices. Phys. Rev. A 94, 042106.

Quantum mechanics: the Bayesian theory generalized to the space of hermitian matrices

@ARTICLE{benavoli2016d,
   title = {Quantum mechanics: the {B}ayesian theory generalized to the space of hermitian matrices},
   journal = {Phys. Rev. A},
   publisher = {American Physical Society},
   volume = {94},
   author = {Benavoli, A. and Facchini, A. and Zaffalon, M.},
   pages = {042106},
   year = {2016},
   doi = {10.1103/PhysRevA.94.042106},
   url = {http://arxiv.org/abs/1605.08177}
}
Download
Benavoli, A., Facchini, A., Zaffalon, M. (2016). Quantum rational preferences and desirability. In Proceedings of the 1st International Workshop on “imperfect Decision Makers: Admitting Real-world Rationality”, Nips 2016 58, pp. 87–96.

Quantum rational preferences and desirability

@INPROCEEDINGS{benavoli2016h,
   title = {Quantum rational preferences and desirability},
   journal = {{ArXiv} {e}-{p}rints 1610.06764},
   volume = {58},
   booktitle = {Proceedings of the 1st International Workshop on ``imperfect Decision Makers: Admitting Real-{w}orld Rationality'', Nips 2016},
   author = {Benavoli, A. and Facchini, A. and Zaffalon, M.},
   pages = {87--96},
   year = {2016},
   doi = {},
   url = {https://proceedings.mlr.press/v58/benavoli17a.html}
}
Download
Benavoli, A., Piga, D. (2016). A probabilistic interpretation of set-membership filtering: application to polynomial systems through polytopic bounding. Automatica 70, pp. 158–172.

A probabilistic interpretation of set-membership filtering: application to polynomial systems through polytopic bounding

@ARTICLE{benavoli2016a,
   title = {A probabilistic interpretation of set-membership filtering: application to polynomial systems through polytopic bounding},
   journal = {Automatica},
   volume = {70},
   author = {Benavoli, A. and Piga, D.},
   pages = {158--172},
   year = {2016},
   doi = {10.1016/j.automatica.2016.03.021},
   url = {}
}
Download
Bucher, D., Cellina, F., Mangili, F., Raubal, M., Rudel, R., Rizzoli, A.E., Elabed, O. (2016). Exploiting fitness apps for sustainable mobility - challenges deploying the GoEco! App. In Proceedings of the 2016 conference ICT for Sustainability, Advances in Computer Science Research, pp. 89–98.

Exploiting fitness apps for sustainable mobility - challenges deploying the GoEco! App

@INPROCEEDINGS{mangili2016c,
   title = {Exploiting fitness apps for sustainable mobility - challenges deploying the {GoEco}! App},
   series = {Advances in Computer Science Research},
   booktitle = {Proceedings of the 2016 {c}onference {ICT} for Sustainability},
   author = {Bucher, D. and Cellina, F. and Mangili, F. and Raubal, M. and Rudel, R. and Rizzoli, A.E. and Elabed, O.},
   pages = {89--98},
   year = {2016},
   doi = {doi:10.2991/ict4s-16.2016.11},
   url = {}
}
Download
Cabañas, R., Antonucci, A., Cano, A., Gómez-Olmedo, M. (2016). Evaluating interval-valued influence diagrams. International Journal of Approximate Reasoning 80, pp. 393–411.

Evaluating interval-valued influence diagrams

@ARTICLE{antonucci2016b,
   title = {Evaluating interval-valued influence diagrams},
   journal = {International Journal of Approximate Reasoning},
   volume = {80},
   author = {Caba\~nas, R. and Antonucci, A. and Cano, A. and G\'omez-Olmedo, M.},
   pages = {393--411},
   year = {2016},
   doi = {10.1016/j.ijar.2016.05.004},
   url = {}
}
Download
de Campos, C.P., Benavoli, A. (2016). Joint analysis of multiple algorithms and performance measures. New Generation Computing, pp. 1–18.

Joint analysis of multiple algorithms and performance measures

@ARTICLE{deCampos2016,
   title = {Joint analysis of multiple algorithms and performance measures},
   journal = {New Generation Computing},
   author = {de Campos, C.P. and Benavoli, A.},
   pages = {1--18},
   year = {2016},
   doi = {10.1007/s00354-016-0005-8},
   url = {http://people.idsia.ch/~alessio/decampos-benavoli-ngc2016.pdf}
}
Download
de Campos, C.P., Corani, G., Scanagatta, M., Cuccu, M., Zaffalon, M. (2016). Learning extended tree augmented naive structures. International Journal of Approximate Reasoning. 68, pp. 153–163.

Learning extended tree augmented naive structures

@ARTICLE{decampos2015a,
   title = {Learning extended tree augmented naive structures},
   journal = {International Journal of Approximate Reasoning.},
   volume = {68},
   author = {de Campos, C.P. and Corani, G. and Scanagatta, M. and Cuccu, M. and Zaffalon, M.},
   pages = {153--163},
   year = {2016},
   doi = {10.1016/j.ijar.2015.04.006},
   url = {}
}
Download
Corani, G., Scanagatta, M. (2016). Air pollution prediction via multi-label classification. Environmental Modelling & Software 80, pp. 259–264.

Air pollution prediction via multi-label classification

@ARTICLE{corani2016a,
   title = {Air pollution prediction via multi-label classification},
   journal = {Environmental Modelling & Software},
   volume = {80},
   author = {Corani, G. and Scanagatta, M.},
   pages = {259--264},
   year = {2016},
   doi = {10.1016/j.envsoft.2016.02.030},
   url = {}
}
Download
Fu, S. (2016). Hierarchical Bayesian LASSO for a negative binomial regression. Journal of Statistical Computation and Simulation.

Hierarchical Bayesian LASSO for a negative binomial regression

@ARTICLE{shuaiFu2015a,
   title = {Hierarchical {B}ayesian {LASSO} for a negative binomial regression},
   journal = {Journal of Statistical Computation and Simulation},
   author = {Fu, S.},
   year = {2016},
   doi = {10.1080/00949655.2015.1106541},
   url = {}
}
Download
Guerciotti, B., Vergara, C., Azzimonti, L., Forzenigo, L., Buora, A., Biondetti, P., Domanin, M. (2016). Computational study of the fluid-dynamics in carotids before and after endarterectomy. Journal of Biomechanics 49(1), pp. 26–38.

Computational study of the fluid-dynamics in carotids before and after endarterectomy

@ARTICLE{azzimonti2016a,
   title = {Computational study of the fluid-dynamics in carotids before and after endarterectomy},
   journal = {Journal of Biomechanics},
   editor = {Elsevier},
   volume = {49},
   author = {Guerciotti, B. and Vergara, C. and Azzimonti, L. and Forzenigo, L. and Buora, A. and Biondetti, P. and Domanin, M.},
   number = {1},
   pages = {26--38},
   year = {2016},
   doi = {10.1016/j.jbiomech.2015.11.009},
   url = {}
}
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Mangili, F. (2016). A prior near-ignorance Gaussian process model for nonparametric regression. International Journal of Approximate Reasoning 78, pp. 153–171.

A prior near-ignorance Gaussian process model for nonparametric regression

@ARTICLE{mangili2016b,
   title = {A prior near-ignorance {G}aussian process model for nonparametric regression},
   journal = {International Journal of Approximate Reasoning },
   volume = {78},
   author = {Mangili, F.},
   pages = {153--171},
   year = {2016},
   doi = {10.1016/j.ijar.2016.07.005},
   url = {}
}
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Mangili, F., Bonesana, C., Antonucci, A., Zaffalon, M., Rubegni, E., Addimando, L. (2016). Adaptive testing by Bayesian networks with application to language assessment. In Micarelli, Alessandro, Stamper, John, Panourgia, Kitty (Eds), Intelligent Tutoring Systems: 13th International Conference, ITS 2016, Zagreb, Croatia, June 7-10, 2016. Proceedings, Lecture Notes in Computer Science, pp. 471–472.

Adaptive testing by Bayesian networks with application to language assessment

@INPROCEEDINGS{mangili2016a,
   title = {Adaptive testing by {B}ayesian networks with application to language assessment},
   editor = {Micarelli, Alessandro and Stamper, John and Panourgia, Kitty},
   series = {Lecture Notes in Computer Science},
   booktitle = {Intelligent Tutoring Systems: 13th International Conference, {ITS} 2016, Zagreb, Croatia, June 7-10, 2016. Proceedings},
   author = {Mangili, F. and Bonesana, C. and Antonucci, A. and Zaffalon, M. and Rubegni, E. and Addimando, L.},
   pages = {471--472},
   year = {2016},
   doi = {},
   url = {http://link.springer.com/content/pdf/bbm%3A978-3-319-39583-8%2F1.pdf}
}
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Mauá, D.D., Antonucci, A., de Campos, C.P. (2016). Hidden Markov models with set-valued parameters. Neurocomputing 180, pp. 94–107.

Hidden Markov models with set-valued parameters

@ARTICLE{antonucci2015c,
   title = {Hidden {M}arkov models with set-valued parameters},
   journal = {Neurocomputing},
   volume = {180},
   author = {Mau\'a, D.D. and Antonucci, A. and de Campos, C.P.},
   pages = {94--107},
   year = {2016},
   doi = {doi:10.1016/j.neucom.2015.08.095},
   url = {}
}
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Miranda, E., Zaffalon, M. (2016). Conformity and independence with coherent lower previsions. International Journal of Approximate Reasoning 78, pp. 125–137.

Conformity and independence with coherent lower previsions

@ARTICLE{zaffalon2016c,
   title = {Conformity and independence with coherent lower previsions},
   journal = {International Journal of Approximate Reasoning},
   volume = {78},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {125--137},
   year = {2016},
   doi = {10.1016/j.ijar.2016.07.004},
   url = {}
}
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Rancoita, P.M.V., Zaffalon, M., Zucca, E., Bertoni, F., de Campos, C.P. (2016). Bayesian network data imputation with application to survival tree analysis. Computational Statistics and Data Analysis 93, pp. 373–387.

Bayesian network data imputation with application to survival tree analysis

@ARTICLE{zaffalon2015b,
   title = {Bayesian network data imputation with application to survival tree analysis},
   journal = {Computational Statistics and Data Analysis},
   volume = {93},
   author = {Rancoita, P.M.V. and Zaffalon, M. and Zucca, E. and Bertoni, F. and de Campos, C.P.},
   pages = {373--387},
   year = {2016},
   doi = {10.1016/j.csda.2014.12.008},
   url = {}
}
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Scanagatta, M., Corani, G., de Campos, C.P., Zaffalon, M. (2016). Learning treewidth-bounded Bayesian networks with thousands of variables. In Daniel D. Lee, Masashi Sugiyama, Ulrike V. Luxburg, Isabelle Guyon, Roman Garnett (Eds), NIPS 2016: Advances in Neural Information Processing Systems 29 29.

Learning treewidth-bounded Bayesian networks with thousands of variables

@INPROCEEDINGS{scanagatta2016a,
   title = {Learning treewidth-bounded {B}ayesian networks with thousands of variables},
   journal = {{NIPS}},
   editor = {Daniel D. Lee and Masashi Sugiyama and Ulrike V. Luxburg and Isabelle Guyon and Roman Garnett},
   volume = {29},
   booktitle = {{NIPS} 2016: Advances in Neural Information Processing Systems 29},
   author = {Scanagatta, M. and Corani, G. and de Campos, C.P. and Zaffalon, M.},
   year = {2016},
   doi = {},
   url = {http://papers.nips.cc/paper/6232-learning-treewidth-bounded-bayesian-networks-with-thousands-of-variables}
}
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2015

Antonucci, A., Corani, G. (2015). The multilabel naive credal classifier. In Augustin, T., Doria, S., Miranda, E., Quaeghebeur, E. (Eds), ISIPTA '15: Proceedings of the Ninth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 27–36.

The multilabel naive credal classifier

@INPROCEEDINGS{antonucci2015a,
   title = {The multilabel naive credal classifier},
   editor = {Augustin, T. and Doria, S. and Miranda, E. and Quaeghebeur, E.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '15: Proceedings of the Ninth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Antonucci, A. and Corani, G.},
   pages = {27--36},
   year = {2015},
   doi = {},
   url = {http://www.sipta.org/isipta15/data/paper/32.pdf}
}
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Antonucci, A., de Rosa, R., Giusti, A., Cuzzolin, F. (2015). Robust classification of multivariate time series by imprecise hidden Markov models. International Journal of Approximate Reasoning 56(B), pp. 249–263.

Robust classification of multivariate time series by imprecise hidden Markov models

@ARTICLE{antonucci2014c,
   title = {Robust classification of multivariate time series by imprecise hidden {M}arkov models},
   journal = {International Journal of Approximate Reasoning},
   volume = {56},
   author = {Antonucci, A. and de Rosa, R. and Giusti, A. and Cuzzolin, F.},
   number = {B},
   pages = {249--263},
   year = {2015},
   doi = {10.1016/j.ijar.2014.07.005},
   url = {}
}
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Antonucci, A., Scanagatta, M., Mauà, D.D., de Campos, C.P. (2015). Early classification of time series by hidden Markov models with set-valued parameters. In Proceedings of the NIPS Time Series Workshop 2015.

Early classification of time series by hidden Markov models with set-valued parameters

@INPROCEEDINGS{antonucci2015d,
   title = {Early classification of time series by hidden {M}arkov models with set-valued parameters},
   booktitle = {Proceedings of the {NIPS} Time Series Workshop 2015},
   author = {Antonucci, A. and Scanagatta, M. and Mau\`a, D.D. and de Campos, C.P.},
   year = {2015},
   doi = {},
   url = {https://sites.google.com/site/nipsts2015/home}
}
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Azzimonti, L., Sangalli, L.M., Secchi, P., Domanin, M., Nobile, F. (2015). Blood flow velocity field estimation via spatial regression with PDE penalization. Journal of the American Statistical Association, Theory and Methods Section 110(511), pp. 1057–1071.

Blood flow velocity field estimation via spatial regression with PDE penalization

@ARTICLE{azzimonti2015a,
   title = {Blood flow velocity field estimation via spatial regression with {PDE} penalization},
   journal = {Journal of the American Statistical Association, Theory and Methods Section},
   volume = {110},
   author = {Azzimonti, L. and Sangalli, L.M. and Secchi, P. and Domanin, M. and Nobile, F.},
   number = {511},
   pages = {1057--1071},
   year = {2015},
   doi = {10.1080/01621459.2014.946036},
   url = {}
}
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Benavoli, A., de Campos, C.P. (2015). Statistical tests for joint analysis of performance measures. In Suzuki, J., Ueno, M. (Eds), Advanced Methodologies for Bayesian Networks: Second International Workshop, Ambn 2015, Yokohama, Japan, November 16-18, 2015. Proceedings 9505, Springer International Publishing, Cham, pp. 76–92.

Statistical tests for joint analysis of performance measures

@INBOOK{Benavoli2015e,
   title = {Statistical tests for joint analysis of performance measures},
   editor = {Suzuki, J. and Ueno, M.},
   publisher = {Springer International Publishing},
   address = {Cham},
   volume = {9505},
   booktitle = {Advanced Methodologies for Bayesian Networks: Second International Workshop, Ambn 2015, Yokohama, Japan, November 16-18, 2015. Proceedings},
   author = {Benavoli, A. and de Campos, C.P.},
   pages = {76--92},
   year = {2015},
   doi = {10.1007/978-3-319-28379-1_6},
   url = {}
}
Download
Benavoli, A., Corani, G., Mangili, F., Zaffalon, M. (2015). A Bayesian nonparametric procedure for comparing algorithms. In Francis Bach, David Blei (Eds), Proceedings of the 32th International Conference on Machine Learning (ICML 2015) 37, pp. 1264–1272.

A Bayesian nonparametric procedure for comparing algorithms

@INPROCEEDINGS{benavoli2015d,
   title = {A {B}ayesian nonparametric procedure for comparing algorithms},
   editor = { Francis Bach and David Blei},
   volume = {37},
   booktitle = {Proceedings of the 32th International Conference on Machine Learning ({ICML} 2015)},
   author = {Benavoli, A. and Corani, G. and Mangili, F. and Zaffalon, M.},
   pages = {1264--1272},
   year = {2015},
   doi = {},
   url = {https://proceedings.mlr.press/v37/benavoli15.html}
}
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Benavoli, A., Mangili, F. (2015). Gaussian processes for Bayesian hypothesis tests on regression functions. In Proceedings of the 18th International Conference on Artificial Intelligence (AISTAT 2015) 38, pp. 74–82.

Gaussian processes for Bayesian hypothesis tests on regression functions

@INPROCEEDINGS{benavoli2015a,
   title = {Gaussian processes for {B}ayesian hypothesis tests on regression functions},
   volume = {38},
   booktitle = {Proceedings of the 18th International Conference on Artificial Intelligence ({AISTAT} 2015)},
   author = {Benavoli, A. and Mangili, F.},
   pages = {74--82},
   year = {2015},
   doi = {},
   url = {http://proceedings.mlr.press/v38/benavoli15.html}
}
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Benavoli, A., Mangili, F., Ruggeri, F., Zaffalon, M. (2015). Imprecise Dirichlet process with application to the hypothesis test on the probability that XY. Journal of Statistical Theory and Practice 9, pp. 658–684.

Imprecise Dirichlet process with application to the hypothesis test on the probability that XY

@ARTICLE{benavoli2015b,
   title = {Imprecise {D}irichlet process with application to the hypothesis test on the probability that {X&le};{Y}},
   journal = {Journal of Statistical Theory and Practice},
   volume = {9},
   author = {Benavoli, A. and Mangili, F. and Ruggeri, F. and Zaffalon, M.},
   pages = {658--684},
   year = {2015},
   doi = {10.1080/15598608.2014.985997},
   url = {}
}
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Cabañas, R., Antonucci, A., Cano, A., Gómez-Olmedo, M. (2015). Variable elimination for interval-valued influence diagrams. In Destercke, S., Denoeux, T. (Eds), Proceedings of the 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2015), Lecture Notes in Computer Science 9161, pp. 541–551.

Variable elimination for interval-valued influence diagrams

@INCOLLECTION{antonucci2015b,
   title = {Variable elimination for interval-valued influence diagrams},
   editor = {Destercke, S. and Denoeux, T.},
   series = {Lecture Notes in Computer Science},
   volume = {9161},
   booktitle = {Proceedings of the 13th European Conference on Symbolic and Quantitative Approaches to Reasoning {w}ith Uncertainty ({ECSQARU} 2015)},
   author = {Caba\~nas, R. and Antonucci, A. and Cano, A. and G\'omez-Olmedo, M.},
   pages = {541--551},
   year = {2015},
   chapter = {Symbolic and Quantitative Approaches to Reasoning with Uncertainty},
   doi = {10.1007/978-3-319-20807-7_49},
   url = {}
}
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de Campos, C.P., Antonucci, A. (2015). Imprecision in machine learning and AI. In The IEEE Intelligent Informatics Bulletin 16(1), IEEE Computer Society, pp. 20–23.

Imprecision in machine learning and AI

@INCOLLECTION{antonucci2015e,
   title = {Imprecision in machine learning and {AI}},
   publisher = {IEEE Computer Society},
   volume = {16},
   booktitle = {The {IEEE} Intelligent Informatics Bulletin},
   author = {de Campos, C.P. and Antonucci, A.},
   number = {1},
   pages = {20--23},
   year = {2015},
   doi = {},
   url = {http://www.comp.hkbu.edu.hk/~cib/2015/Dec/iib_vol16no1.pdf}
}
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Corani, G., Benavoli, A. (2015). A Bayesian approach for comparing cross-validated algorithms on multiple data sets. Machine Learning 100(2), pp. 285–304.

A Bayesian approach for comparing cross-validated algorithms on multiple data sets

@ARTICLE{corani2015b,
   title = {A {B}ayesian approach for comparing cross-validated algorithms on multiple data sets},
   journal = {Machine Learning},
   volume = {100},
   author = {Corani, G. and Benavoli, A.},
   number = {2},
   pages = {285--304},
   year = {2015},
   doi = {10.1007/s10994-015-5486-z},
   url = {}
}
Download
Corani, G., Benavoli, A., Mangili, F., Zaffalon, M. (2015). Bayesian hypothesis testing in machine learning. In Proc. ECML PKDD 2015 (European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases), pp. 199–202.

Bayesian hypothesis testing in machine learning

@INPROCEEDINGS{corani2015c,
   title = {Bayesian hypothesis testing in machine learning},
   booktitle = {Proc. {ECML} {PKDD} 2015 (European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases)},
   author = {Corani, G. and Benavoli, A. and Mangili, F. and Zaffalon, M.},
   pages = {199--202},
   year = {2015},
   doi = {10.1007/978-3-319-23461-8_13},
   url = {}
}
Download
Corani, G., Mignatti, A. (2015). Credal model averaging for classification: representing prior ignorance and expert opinions.. International Journal of Approximate Reasoning 56(B), pp. 264–277.

Credal model averaging for classification: representing prior ignorance and expert opinions.

@ARTICLE{corani2014a,
   title = {Credal model averaging for classification: representing prior ignorance and expert opinions.},
   journal = {International Journal of Approximate Reasoning},
   volume = {56},
   author = {Corani, G. and Mignatti, A.},
   number = {B},
   pages = {264--277},
   year = {2015},
   doi = {10.1016/j.ijar.2014.07.001},
   url = {}
}
Download
Corani, G., Mignatti, A. (2015). Robust Bayesian model averaging for the analysis of presence–absence data. Environmental and Ecological Statistics 22(3), pp. 513–534.

Robust Bayesian model averaging for the analysis of presence–absence data

@ARTICLE{corani2015a,
   title = {Robust {B}ayesian model averaging for the analysis of presence--absence data},
   journal = {Environmental and Ecological Statistics},
   volume = {22},
   author = {Corani, G. and Mignatti, A.},
   number = {3},
   pages = {513--534},
   year = {2015},
   doi = {10.1007/s10651-014-0308-1},
   url = {}
}
Download
Fu, S. (2015). A hierarchical Bayesian approach to negative binomial regression. Methods and Applications of Analysis 22(4), pp. 409–428.

A hierarchical Bayesian approach to negative binomial regression

@ARTICLE{shuaiFu2015b,
   title = {A hierarchical {B}ayesian approach to negative binomial regression},
   journal = {Methods and Applications of Analysis},
   volume = {22},
   author = {Fu, S.},
   number = {4},
   pages = {409--428},
   year = {2015},
   doi = {10.4310/MAA.2015.v22.n4.a4},
   url = {}
}
Download
Mangili, F. (2015). A prior near-ignorance Gaussian Process model for nonparametric regression. In Augustin,T., Doria, S., Miranda, E., Quaeghebeur, E. (Eds), ISIPTA '15: Proceedings of the Ninth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 187–196.

A prior near-ignorance Gaussian Process model for nonparametric regression

@INPROCEEDINGS{mangili2015b,
   title = {A prior near-ignorance {G}aussian {P}rocess model for nonparametric regression},
   editor = {Augustin,T. and Doria, S. and Miranda, E. and Quaeghebeur, E.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '15: Proceedings of the Ninth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Mangili, F.},
   pages = {187--196},
   year = {2015},
   doi = {},
   url = {http://www.sipta.org/isipta15/data/paper/15.pdf}
}
Download
Mangili, F., Benavoli, A. (2015). New prior near-ignorance models on the simplex. International Journal of Approximate Reasoning 56(Part B), pp. 278–306.

New prior near-ignorance models on the simplex

@ARTICLE{Mangili2014a,
   title = {New prior near-ignorance models on the simplex},
   journal = {International Journal of Approximate Reasoning},
   volume = {56},
   author = {Mangili, F. and Benavoli, A.},
   number = {Part B},
   pages = {278--306},
   year = {2015},
   doi = {10.1016/j.ijar.2014.08.005},
   url = {}
}
Download
Mangili, F., Benavoli, A., de Campos, C.P., Zaffalon, M. (2015). Reliable survival analysis based on the Dirichlet Process. Biometrical Journal 57(6), pp. 1002–1019.

Reliable survival analysis based on the Dirichlet Process

@ARTICLE{mangili2015a,
   title = {Reliable survival analysis based on the {D}irichlet {P}rocess},
   journal = {Biometrical Journal},
   volume = {57},
   author = {Mangili, F. and Benavoli, A. and de Campos, C.P. and Zaffalon, M.},
   number = {6},
   pages = {1002--1019},
   year = {2015},
   doi = {10.1002/bimj.201500062},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2015). On the problem of computing the conglomerable natural extension. International Journal of Approximate Reasoning 56(A), pp. 1–27.

On the problem of computing the conglomerable natural extension

@ARTICLE{zaffalon2014b,
   title = {On the problem of computing the conglomerable natural extension},
   journal = {International Journal of Approximate Reasoning},
   volume = {56},
   author = {Miranda, E. and Zaffalon, M.},
   number = {A},
   pages = {1--27},
   year = {2015},
   doi = {10.1016/j.ijar.2014.09.003},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2015). Independent products in infinite spaces. Journal of Mathematical Analysis and Applications 425(1), pp. 460–488.

Independent products in infinite spaces

@ARTICLE{zaffalon2015a,
   title = {Independent products in infinite spaces},
   journal = {Journal of Mathematical Analysis and Applications},
   volume = {425},
   author = {Miranda, E. and Zaffalon, M.},
   number = {1},
   pages = {460--488},
   year = {2015},
   doi = {10.1016/j.jmaa.2014.12.049},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2015). Conformity and independence with coherent lower previsions. In Augustin,T., Doria, S., Miranda, E., Quaeghebeur, E. (Eds), ISIPTA '15: Proceedings of the Ninth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 197–206.

Conformity and independence with coherent lower previsions

@INPROCEEDINGS{zaffalon2015c,
   title = {Conformity and independence with coherent lower previsions},
   editor = {Augustin,T. and Doria, S. and Miranda, E. and Quaeghebeur, E.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '15: Proceedings of the Ninth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {197--206},
   year = {2015},
   doi = {},
   url = {http://www.sipta.org/isipta15/data/paper/16.pdf}
}
Download
Scanagatta, M., de Campos, C.P., Corani, G., Zaffalon, M. (2015). Learning Bayesian networks with thousands of variables. In Corinna Cortes, Neil D. Lawrence, Daniel D. Lee, Masashi Sugiyama, Roman Garnett (Eds), NIPS 2015: Advances in Neural Information Processing Systems 28 28.

Learning Bayesian networks with thousands of variables

@INPROCEEDINGS{scanagatta2015a,
   title = {Learning {B}ayesian networks with thousands of variables},
   journal = {{NIPS}},
   editor = {Corinna Cortes and Neil D. Lawrence and Daniel D. Lee and Masashi Sugiyama and Roman Garnett},
   volume = {28},
   booktitle = {{NIPS} 2015: Advances in Neural Information Processing Systems 28},
   author = {Scanagatta, M. and de Campos, C.P. and Corani, G. and Zaffalon, M.},
   year = {2015},
   doi = {},
   url = {http://papers.nips.cc/paper/5803-learning-bayesian-networks-with-thousands-of-variables}
}
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2014

Antonucci, A., de Campos, C.P., Huber, D., Zaffalon, M. (2014). Approximate credal network updating by linear programming with applications to decision making. International Journal of Approximate Reasoning 58, pp. 25–38.

Approximate credal network updating by linear programming with applications to decision making

@ARTICLE{antonucci2014e,
   title = {Approximate credal network updating by linear programming with applications to decision making},
   journal = {International Journal of Approximate Reasoning},
   volume = {58},
   author = {Antonucci, A. and de Campos, C.P. and Huber, D. and Zaffalon, M.},
   pages = {25--38},
   year = {2014},
   doi = {10.1016/j.ijar.2014.10.003},
   url = {}
}
Download
Antonucci, A., de Campos, C.P., Zaffalon, M. (2014). Probabilistic graphical models. In Augustin, T., Coolen, F., de Cooman, G., Troffaes, M. (Eds), Introduction to Imprecise Probabilities, Wiley, pp. 207–229.

Probabilistic graphical models

@INBOOK{antonucci2014a,
   title = {Probabilistic graphical models},
   editor = {Augustin, T. and Coolen, F. and de Cooman, G. and Troffaes, M.},
   publisher = {Wiley},
   booktitle = {Introduction to Imprecise Probabilities},
   author = {Antonucci, A. and de Campos, C.P. and Zaffalon, M.},
   pages = {207--229},
   year = {2014},
   chapter = {9},
   doi = {10.1002/9781118763117.ch9},
   url = {}
}
Download
Antonucci, A., Karlsson, A., Sundgren, D. (2014). Decision making with hierarchical credal sets. In Laurent, A., Strauss, O., Bouchon-Meunier, B., Yager, R.R. (Eds), Information Processing and Management of Uncertainty in Knowledge-based Systems, Communications in Computer and Information Science 444, Springer, pp. 456–465.

Decision making with hierarchical credal sets

@INPROCEEDINGS{antonucci2014b,
   title = {Decision making with hierarchical credal sets},
   editor = {Laurent, A. and Strauss, O. and Bouchon-Meunier, B. and Yager, R.R.},
   publisher = {Springer},
   series = {Communications in Computer and Information Science},
   volume = {444},
   booktitle = {Information Processing and Management of Uncertainty in Knowledge-{b}ased Systems},
   author = {Antonucci, A. and Karlsson, A. and Sundgren, D.},
   pages = {456--465},
   year = {2014},
   doi = {10.1007/978-3-319-08852-5_47},
   url = {}
}
Download
Azzimonti, L., Nobile, F., Sangalli, L.M., Secchi, P. (2014). Mixed finite elements for spatial regression with PDE penalization. SIAM/ASA Journal on Uncertainty Quantification 2(1), pp. 305–335.

Mixed finite elements for spatial regression with PDE penalization

@ARTICLE{azzimonti2014a,
   title = {Mixed finite elements for spatial regression with {PDE} penalization},
   journal = {{SIAM/ASA} Journal on Uncertainty Quantification},
   volume = {2},
   author = {Azzimonti, L. and Nobile, F. and Sangalli, L.M. and Secchi, P.},
   number = {1},
   pages = {305--335},
   year = {2014},
   doi = {10.1137/130925426},
   url = {}
}
Download
Benavoli, A. (2014). Belief function and multivalued mapping robustness in statistical estimation. International Journal of Approximate Reasoning 55(1, Part 3), pp. 311–329.

Belief function and multivalued mapping robustness in statistical estimation

@ARTICLE{benavoli2013a,
   title = {Belief function and multivalued mapping robustness in statistical estimation},
   journal = {International Journal of Approximate Reasoning},
   volume = {55},
   author = {Benavoli, A.},
   number = {1, Part 3},
   pages = {311--329},
   year = {2014},
   doi = {10.1016/j.ijar.2013.04.014},
   url = {}
}
Download
Benavoli, A., Mangili, F., Corani, G., Zaffalon, M., Ruggeri, F. (2014). A Bayesian Wilcoxon signed-rank test based on the Dirichlet process. In Eric P. Xing, Tony Jebara (Eds), Proceedings of the 31st International Conference on Machine Learning (ICML 2014) 32(2), pp. 1026–1034.

A Bayesian Wilcoxon signed-rank test based on the Dirichlet process

@INPROCEEDINGS{benavoli2014a,
   title = {A {B}ayesian {W}ilcoxon signed-rank test based on the {D}irichlet process},
   editor = { Eric P. Xing and Tony Jebara},
   volume = {32},
   booktitle = {Proceedings of the 31st International Conference on Machine Learning ({ICML} 2014)},
   author = {Benavoli, A. and Mangili, F. and Corani, G. and Zaffalon, M. and Ruggeri, F.},
   number = {2},
   pages = {1026--1034},
   year = {2014},
   doi = {},
   url = {http://proceedings.mlr.press/v32/benavoli14.html}
}
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Benavoli, A., Zaffalon, M. (2014). Prior near ignorance for inferences in the k-parameter exponential family. Statistics 49, pp. 1104–1140.

Prior near ignorance for inferences in the k-parameter exponential family

@ARTICLE{benavoli2014b,
   title = {Prior near ignorance for inferences in the k-parameter exponential family},
   journal = {Statistics},
   volume = {49},
   author = {Benavoli, A. and Zaffalon, M.},
   pages = {1104--1140},
   year = {2014},
   doi = {10.1080/02331888.2014.960869},
   url = {}
}
Download
De Bock, J., de Campos, C.P., Antonucci, A. (2014). Global sensitivity analysis for MAP inference in graphical models. In Ghahramani, Z., Welling, M., Cortes, C., Lawrence, N.D. , Weinberger, K.Q. (Eds), Advances in Neural Information Processing Systems 27 (NIPS 2014), Curran Associates, Inc., pp. 2690–2698.

Global sensitivity analysis for MAP inference in graphical models

@INCOLLECTION{antonucci2014f,
   title = {Global sensitivity analysis for {MAP} inference in graphical models},
   editor = {Ghahramani, Z. and Welling, M. and Cortes, C. and Lawrence, N.D. and Weinberger, K.Q. },
   publisher = {Curran Associates, Inc.},
   booktitle = {Advances in Neural Information Processing Systems 27 ({NIPS} 2014)},
   author = {De Bock, J. and de Campos, C.P. and Antonucci, A.},
   pages = {2690--2698},
   year = {2014},
   doi = {},
   url = {https://proceedings.neurips.cc/paper/2014/hash/0966289037ad9846c5e994be2a91bafa-Abstract.html}
}
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de Campos, C.P., Cuccu, M., Corani, G., Zaffalon, M. (2014). Extended tree augmented naive classifier. In van der Gaag, L., Feelders, A. (Ed), PGM'14: Proceedings of the Seventh European Workshop on Probabilistic Graphical Models, Lecture Notes in Artificial Intelligence 8754, Springer, pp. 176–189.

Extended tree augmented naive classifier

@INPROCEEDINGS{decampos2014a,
   title = {Extended tree augmented naive classifier},
   editor = {van der Gaag, L., Feelders, A.},
   publisher = {Springer},
   series = {Lecture Notes in Artificial Intelligence},
   volume = {8754},
   booktitle = {{PGM'14}: Proceedings of the Seventh European Workshop on Probabilistic Graphical Models},
   author = {de Campos, C.P. and Cuccu, M. and Corani, G. and Zaffalon, M.},
   pages = {176--189},
   year = {2014},
   doi = {10.1007/978-3-319-11433-0_12},
   url = {}
}
Download
Corani, G., Abellán, J., Masegosa, A., Moral, S., Zaffalon, M. (2014). Classification. In Augustin,T., Coolen,F., de Cooman,G., Troffaes,M. (Eds), Introduction to Imprecise Probabilities, Wiley, pp. 261–285.

Classification

@INCOLLECTION{corani2013b,
   title = {Classification},
   editor = {Augustin,T. and Coolen,F. and de Cooman,G. and Troffaes,M.},
   publisher = {Wiley},
   booktitle = {Introduction to Imprecise Probabilities},
   author = {Corani, G. and Abell\'an, J. and Masegosa, A. and Moral, S. and Zaffalon, M.},
   pages = {261--285},
   year = {2014},
   chapter = {10},
   doi = {},
   url = {http://eu.wiley.com/WileyCDA/WileyTitle/productCd-0470973811.html}
}
Download
Corani, G., Antonucci, A. (2014). Credal Ensembles of Classifiers. Computational Statistics & Data Analysis 71, pp. 818–831.

Credal Ensembles of Classifiers

@ARTICLE{corani2012f,
   title = {Credal {E}nsembles of {C}lassifiers},
   journal = {Computational Statistics & Data Analysis},
   volume = {71},
   author = {Corani, G. and Antonucci, A.},
   pages = {818--831},
   year = {2014},
   doi = {10.1016/j.csda.2012.11.010},
   url = {}
}
Download
Corani, G., Antonucci, A., Mauá, D., Gabaglio, S. (2014). Trading off Speed and Accuracy in Multilabel Classification. In van der Gaag, L., Feelders, A. (Eds), PGM'14: Proceedings of the Seventh European Workshop on Probabilistic Graphical Models, Lecture Notes in Artificial Intelligence 8754, Springer, pp. 145–159.

Trading off Speed and Accuracy in Multilabel Classification

@INPROCEEDINGS{corani2014b,
   title = {Trading off {S}peed and {A}ccuracy in {M}ultilabel {C}lassification},
   journal = {Proc. 7th European Workshop on Probabilistic Graphical Models ({PGM} '14)},
   editor = {van der Gaag, L. and Feelders, A.},
   publisher = {Springer},
   series = {Lecture Notes in Artificial Intelligence},
   volume = {8754},
   booktitle = {{PGM'14}: Proceedings of the Seventh European Workshop on Probabilistic Graphical Models},
   author = {Corani, G. and Antonucci, A. and Mau\'a, D. and Gabaglio, S.},
   pages = {145--159},
   year = {2014},
   doi = {10.1007/978-3-319-11433-0_10},
   url = {}
}
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Cozman, F.G., de Campos, C.P. (2014). Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms. International Journal of Approximate Reasoning 55(2), pp. 666–682.

Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms

@ARTICLE{cozman2013ijar,
   title = {Kuznetsov independence for interval-valued expectations and sets of probability distributions: {P}roperties and algorithms},
   journal = {International Journal of Approximate Reasoning},
   publisher = {Elsevier},
   volume = {55},
   author = {Cozman, F.G. and de Campos, C.P.},
   number = {2},
   pages = {666--682},
   year = {2014},
   doi = {10.1016/j.ijar.2013.09.013},
   url = {}
}
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Mauá, D.D., de Campos, C.P., Antonucci, A. (2014). Hidden Markov models with imprecisely specified parameters. In Proceedings of the Brazilian Conference on Intelligent Systems, pp. 186–191.

Hidden Markov models with imprecisely specified parameters

@INPROCEEDINGS{antonucci2014d,
   title = {Hidden {M}arkov models with imprecisely specified parameters},
   booktitle = {Proceedings of the Brazilian Conference on Intelligent Systems},
   author = {Mau\'a, D.D. and de Campos, C.P. and Antonucci, A.},
   pages = {186--191},
   year = {2014},
   doi = {10.1109/BRACIS.2014.42},
   url = {}
}
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Mauá, D.D., de Campos, C.P., Benavoli, A., Antonucci, A. (2014). Probabilistic inference in credal networks: new complexity results. Journal of Artifical Intelligence Research 50, pp. 603–637.

Probabilistic inference in credal networks: new complexity results

@ARTICLE{maua14jair,
   title = {Probabilistic inference in credal networks: new complexity results},
   journal = {Journal of Artifical Intelligence Research},
   volume = {50},
   author = {Mau\'a, D.D. and de Campos, C.P. and Benavoli, A. and Antonucci, A.},
   pages = {603--637},
   year = {2014},
   doi = {10.1613/jair.4355},
   url = {}
}
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Polpo, A., de Campos, C.P., Sinha, D., Lipsitz, S., Lin, J. (2014). Transform both sides model: a parametric approach. Computational Statistics and Data Analysis 71, pp. 903–913.

Transform both sides model: a parametric approach

@ARTICLE{decampos2013b,
   title = {Transform both sides model: a parametric approach},
   journal = {Computational Statistics and Data Analysis},
   publisher = {Elsevier},
   volume = {71},
   author = {Polpo, A. and de Campos, C.P. and Sinha, D. and Lipsitz, S. and Lin, J.},
   pages = {903--913},
   year = {2014},
   doi = {10.1016/j.csda.2013.07.023},
   url = {}
}
Download
Scanagatta, M., de Campos, C.P., Zaffalon, M. (2014). Min-BDeu and max-BDeu scores for learning Bayesian networks. In van der Gaag, L., Feelders, A. (Eds), PGM'14: Proceedings of the Seventh European Workshop on Probabilistic Graphical Models, Lecture Notes in Artificial Intelligence 8754, Springer, pp. 426–441.

Min-BDeu and max-BDeu scores for learning Bayesian networks

@INPROCEEDINGS{scanagatta2014a,
   title = {Min-{BDeu} and max-{BDeu} scores for learning {B}ayesian networks},
   editor = {van der Gaag, L. and Feelders, A.},
   publisher = {Springer},
   series = {Lecture Notes in Artificial Intelligence},
   volume = {8754},
   booktitle = {{PGM'14}: Proceedings of the Seventh European Workshop on Probabilistic Graphical Models},
   author = {Scanagatta, M. and de Campos, C.P. and Zaffalon, M.},
   pages = {426--441},
   year = {2014},
   doi = {10.1007/978-3-319-11433-0_28},
   url = {}
}
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Zaffalon, M., Corani, G. (2014). Comments on "Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks" by Andrés R. Masegosa and Serafín Moral. International Journal of Approximate Reasoning 55(7), pp. 1597–1600.

Comments on "Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks" by Andrés R. Masegosa and Serafín Moral

@ARTICLE{zaffalon2014a,
   title = {Comments on {"Imprecise} probability models for learning multinomial distributions from data. Applications to learning credal networks" by {A}ndr\'es {R}. Masegosa and {S}eraf\'in {M}oral},
   journal = {International Journal of Approximate Reasoning},
   volume = {55},
   author = {Zaffalon, M. and Corani, G.},
   number = {7},
   pages = {1597--1600},
   year = {2014},
   doi = {10.1016/j.ijar.2014.05.001},
   url = {}
}
Download
top

2013

Antonucci, A., de Campos, C.P., Huber, D., Zaffalon, M. (2013). Approximating credal network inferences by linear programming. In van der Gaag, L. C. (Ed), Proceedings of the 12th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Lecture Notes in Artificial Intelligence 7958, Springer, Berlin Heidelberg, pp. 13–25.

Approximating credal network inferences by linear programming

@INPROCEEDINGS{antonucci2013a,
   title = {Approximating credal network inferences by linear programming},
   editor = {van der Gaag, L. C.},
   publisher = {Springer},
   address = {Berlin Heidelberg},
   series = {Lecture Notes in Artificial Intelligence},
   volume = {7958},
   booktitle = {Proceedings of the 12th European Conference on Symbolic and Quantitative Approaches to Reasoning {w}ith Uncertainty},
   author = {Antonucci, A. and de Campos, C.P. and Huber, D. and Zaffalon, M.},
   pages = {13--25},
   year = {2013},
   doi = {10.1007/978-3-642-39091-3_2},
   url = {}
}
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Antonucci, A., Corani, G., Mauá, D.D., Gabaglio, S. (2013). An ensemble of Bayesian networks for multilabel classification. In Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI-13), pp. 1220–1225.

An ensemble of Bayesian networks for multilabel classification

@INPROCEEDINGS{antonucci2013d,
   title = {An ensemble of {B}ayesian networks for multilabel classification},
   booktitle = {Proceedings of the 23rd International Joint Conference on Artificial Intelligence ({IJCAI}-13)},
   author = {Antonucci, A. and Corani, G. and Mau\'a, D.D. and Gabaglio, S.},
   pages = {1220--1225},
   year = {2013},
   doi = {},
   url = {}
}
Download
Antonucci, A., Huber, D., Zaffalon, M., Luginbuehl, P., Chapman, I., Ladouceur, R. (2013). CREDO: a military decision-support system based on credal networks. In Proceedings of the 16th Conference on Information Fusion (FUSION 2013), pp. 1–8.

CREDO: a military decision-support system based on credal networks

@INPROCEEDINGS{antonucci2013c,
   title = {{CREDO}: a military decision-support system based on credal networks},
   booktitle = {Proceedings of the 16th Conference on Information Fusion ({FUSION} 2013)},
   author = {Antonucci, A. and Huber, D. and Zaffalon, M. and Luginbuehl, P. and Chapman, I. and Ladouceur, R.},
   pages = {1--8},
   year = {2013},
   doi = {},
   url = {}
}
Download
Antonucci, A., de Rosa, R., Giusti, A., Cuzzolin, F. (2013). Temporal data classification by imprecise dynamical models. In Cozman, F.G., Denoeux, T., Destercke, S., Seidenfeld, T. (Eds), ISIPTA '13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 13–22.

Temporal data classification by imprecise dynamical models

@INPROCEEDINGS{antonucci2013b,
   title = {Temporal data classification by imprecise dynamical models},
   editor = {Cozman, F.G. and Denoeux, T. and Destercke, S. and Seidenfeld, T.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Antonucci, A. and de Rosa, R. and Giusti, A. and Cuzzolin, F.},
   pages = {13--22},
   year = {2013},
   doi = {},
   url = {http://www.sipta.org/isipta13/proceedings/papers/s002.pdf}
}
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Azzimonti, L., Ieva, F., Paganoni, A.M. (2013). Nonlinear nonparametric mixed-effects models for unsupervised classification. Computational Statistics 28(4), pp. 1549–1570.

Nonlinear nonparametric mixed-effects models for unsupervised classification

@ARTICLE{azzimonti2013a,
   title = {Nonlinear nonparametric mixed-effects models for unsupervised classification},
   journal = {Computational Statistics},
   volume = {28},
   author = {Azzimonti, L. and Ieva, F. and Paganoni, A.M.},
   number = {4},
   pages = {1549--1570},
   year = {2013},
   doi = {10.1007/s00180-012-0366-5},
   url = {}
}
Download
Benavoli, A. (2013). The generalised moment-based filter. Automatic Control, IEEE Transactions on 58(10), pp. 2642–2647.

The generalised moment-based filter

@ARTICLE{benavoli2013b,
   title = {The generalised moment-based filter},
   journal = {Automatic Control, {IEEE} Transactions on},
   volume = {58},
   author = {Benavoli, A.},
   number = {10},
   pages = {2642--2647},
   year = {2013},
   doi = {10.1109/TAC.2013.2255971},
   url = {}
}
Download
Benavoli, A. (2013). Imprecise hierarchical Dirichlet model with applications. In Information Fusion (fusion), 2013 Proc. Of the 16th International Conference on, pp. 1918–1925.

Imprecise hierarchical Dirichlet model with applications

@INPROCEEDINGS{benavoli2013d,
   title = {Imprecise hierarchical {D}irichlet model with applications},
   booktitle = {Information Fusion ({f}usion), 2013 Proc. Of the 16th International Conference on},
   author = {Benavoli, A.},
   pages = {1918--1925},
   year = {2013},
   doi = {},
   url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6641239&isnumber=6641065}
}
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Benavoli, A., Papi, F. (2013). Set-membership PHD filter. In Information Fusion (fusion), 2013 Proc. Of the 16th International Conference on, pp. 1722–1729.

Set-membership PHD filter

@INPROCEEDINGS{benavoli2013c,
   title = {Set-membership {PHD} filter},
   booktitle = {Information Fusion ({f}usion), 2013 Proc. Of the 16th International Conference on},
   author = {Benavoli, A. and Papi, F.},
   pages = {1722--1729},
   year = {2013},
   doi = {},
   url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6641211&isnumber=6641065}
}
Download
Benavoli, A., Zaffalon, M. (2013). Density-ratio robustness in dynamic state estimation. Mechanical Systems and Signal Processing 37(1–2), pp. 54–75.

Density-ratio robustness in dynamic state estimation

@ARTICLE{benavoli2012g,
   title = {Density-ratio robustness in dynamic state estimation},
   journal = {Mechanical Systems and Signal Processing},
   volume = {37},
   author = {Benavoli, A. and Zaffalon, M.},
   number = {1--2},
   pages = {54--75},
   year = {2013},
   doi = {10.1016/j.ymssp.2012.09.004},
   url = {http://www.idsia.ch/~alessio/benavoli2012g.pdf}
}
Download
de Campos, C.P., Cozman, F.G. (2013). Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks. In Proceedings of the 27th AAAI Conference on Advances in Artificial Intelligence (AAAI), pp. 217–223.

Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks

@INPROCEEDINGS{decampos2013a,
   title = {Complexity of inferences in polytree-shaped semi-qualitative probabilistic networks},
   booktitle = {Proceedings of the 27th {AAAI} Conference on Advances in Artificial Intelligence ({AAAI})},
   author = {de Campos, C.P. and Cozman, F.G.},
   pages = {217--223},
   year = {2013},
   doi = {},
   url = {}
}
Download
de Campos, C.P., Rancoita, P.M.V., Kwee, I., Zucca, E., Zaffalon, M., Bertoni, F. (2013). Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices. PLoS ONE 8(11), e79720.

Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices

@ARTICLE{decampos2013d,
   title = {Discovering subgroups of patients from {DNA} copy number data using {NMF} on compacted matrices},
   journal = {{PLoS} {ONE}},
   volume = {8},
   author = {de Campos, C.P. and Rancoita, P.M.V. and Kwee, I. and Zucca, E. and Zaffalon, M. and Bertoni, F.},
   number = {11},
   pages = {e79720},
   year = {2013},
   doi = {10.1371/journal.pone.0079720},
   url = {}
}
Download
Corani, G., Magli, M., Giusti, A., Gianaroli, L., Gambardella, L. (2013). A Bayesian network model for predicting pregnancy after in vitro fertilization. Computers in Biology and Medicine 43(11), pp. 1783–1792.

A Bayesian network model for predicting pregnancy after in vitro fertilization

@ARTICLE{corani2013c,
   title = {A {B}ayesian network model for predicting pregnancy after in vitro fertilization},
   journal = {Computers in Biology and Medicine},
   volume = {43},
   author = {Corani, G. and Magli, M. and Giusti, A. and Gianaroli, L. and Gambardella, L.},
   number = {11},
   pages = {1783--1792},
   year = {2013},
   doi = {10.1016/j.compbiomed.2013.07.035},
   url = {}
}
Download
Corani, G., Mignatti, A. (2013). Credal model averaging of logistic regression for modeling the distribution of marmot burrows. In Cozman, F.G., Denoeux, T., Destercke, S., Seidenfeld, T. (Eds),, pp. 233–243.

Credal model averaging of logistic regression for modeling the distribution of marmot burrows

@INPROCEEDINGS{corani2013a,
   title = {Credal model averaging of logistic regression for modeling the distribution of marmot burrows},
   journal = {Proceedings of {ISIPTA} '13 (the Eighth International Symposium on Imprecise Probability: Theories and Applications)},
   editor = {Cozman, F.G. and Denoeux, T. and Destercke, S. and Seidenfeld, T. },
   author = {Corani, G. and Mignatti, A.},
   pages = {233--243},
   year = {2013},
   doi = {},
   url = {}
}
Download
Gianaroli, L., Magli, M.C., Gambardella, L., Giusti, A., Grugnetti, C., Corani, G. (2013). Objective way to support embryo transfer: a probabilistic decision. Human Reproduction 28(5), pp. 1210–1220.

Objective way to support embryo transfer: a probabilistic decision

@ARTICLE{corani2013d,
   title = {Objective way to support embryo transfer: a probabilistic decision},
   journal = {Human Reproduction},
   volume = {28},
   author = {Gianaroli, L. and Magli, M.C. and Gambardella, L. and Giusti, A. and Grugnetti, C. and Corani, G.},
   number = {5},
   pages = {1210--1220},
   year = {2013},
   doi = {10.1093/humrep/det030},
   url = {}
}
Download
von Hohenstaufen, K.A., Conconi, A., de Campos, C.P., Franceschetti, S., Bertoni, F., Margiotta Casaluci, G., Stathis, A., Ghielmini, M., Stussi, G., Cavalli, F., Gaidano, G., Zucca, E. (2013). Prognostic impact of monocyte count at presentation in mantle cell lymphoma. British Journal of Haematology 162(4), pp. 465–473.

Prognostic impact of monocyte count at presentation in mantle cell lymphoma

@ARTICLE{decampos2013c,
   title = {Prognostic impact of monocyte count at presentation in mantle cell lymphoma},
   journal = {British Journal of Haematology},
   publisher = {Blackwell Publishing Ltd},
   volume = {162},
   author = {von Hohenstaufen, K.A. and Conconi, A. and de Campos, C.P. and Franceschetti, S. and Bertoni, F. and Margiotta Casaluci, G. and Stathis, A. and Ghielmini, M. and Stussi, G. and Cavalli, F. and Gaidano, G. and Zucca, E.},
   number = {4},
   pages = {465--473},
   year = {2013},
   doi = {10.1111/bjh.12409},
   url = {http://onlinelibrary.wiley.com/doi/10.1111/bjh.12409/pdf}
}
Download
Mangili, F., Benavoli, A. (2013). New prior near-ignorance models on the simplex. In Cozman, F.G., Denoeux, T., Destercke, S., Seidenfeld, T. (Eds), ISIPTA '13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, Compiegne (FR), pp. 1–9.

New prior near-ignorance models on the simplex

@INPROCEEDINGS{mangili2013a,
   title = {New prior near-ignorance models on the simplex},
   editor = {Cozman, F.G. and Denoeux, T. and Destercke, S. and Seidenfeld, T.},
   publisher = {SIPTA},
   address = {Compiegne (FR)},
   booktitle = {{ISIPTA };'13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Mangili, F. and Benavoli, A.},
   pages = {1--9},
   year = {2013},
   doi = {},
   url = {}
}
Download
Mauá, D.D., de Campos, C.P., Benavoli, A., Antonucci, A. (2013). On the complexity of strong and epistemic credal networks. In Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence, AUAI Press, pp. 391–400.

On the complexity of strong and epistemic credal networks

@INPROCEEDINGS{maua2013a,
   title = {On the complexity of strong and epistemic credal networks},
   publisher = {AUAI Press},
   booktitle = {Proceedings of the 29th Conference on Uncertainty in Artificial Intelligence},
   author = {Mau\'a, D.D. and de Campos, C.P. and Benavoli, A. and Antonucci, A.},
   pages = {391--400},
   year = {2013},
   doi = {},
   url = {}
}
Download
Mauá, D.D., de Campos, C.P., Zaffalon, M. (2013). On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables. Artificial Intelligence 205, pp. 30–38.

On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables

@ARTICLE{maua2013b,
   title = {On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables},
   journal = {Artificial Intelligence},
   volume = {205},
   author = {Mau\'a, D.D. and de Campos, C.P. and Zaffalon, M.},
   pages = {30--38},
   year = {2013},
   doi = {10.1016/j.artint.2013.10.002},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2013). Conglomerable coherent lower previsions. In Kruse, R., Berthold, M. R., Moewes, C., Gil, M. A., Grzegorzewski, P., Hryniewicz, O. (Eds), Synergies of Soft Computing and Statistics for Intelligent Data Analysis, Advances in Intelligent and Soft Computing 190, Springer Berlin Heidelberg, pp. 419–427.

Conglomerable coherent lower previsions

@INCOLLECTION{zaffalon2012a,
   title = {Conglomerable coherent lower previsions},
   editor = {Kruse, R. and Berthold, M. R. and Moewes, C. and Gil, M. A. and Grzegorzewski, P. and Hryniewicz, O.},
   publisher = {Springer Berlin Heidelberg},
   series = {Advances in Intelligent and Soft Computing},
   volume = {190},
   booktitle = {Synergies of Soft Computing and Statistics for Intelligent Data Analysis},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {419--427},
   year = {2013},
   doi = {10.1007/978-3-642-33042-1_45},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2013). Conglomerable coherence. International Journal of Approximate Reasoning 54(9), pp. 1322–1350.

Conglomerable coherence

@ARTICLE{zaffalon2013b,
   title = {Conglomerable coherence},
   journal = {International Journal of Approximate Reasoning},
   volume = {54},
   author = {Miranda, E. and Zaffalon, M.},
   number = {9},
   pages = {1322--1350},
   year = {2013},
   doi = {10.1016/j.ijar.2013.04.016},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2013). Computing the conglomerable natural extension. In Cozman, F., Denoeux, T., Destercke, S., Seidenfeld, T. (Eds), ISIPTA '13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 255–264.

Computing the conglomerable natural extension

@INPROCEEDINGS{zaffalon2013c,
   title = {Computing the conglomerable natural extension},
   editor = {Cozman, F. and Denoeux, T. and Destercke, S. and Seidenfeld, T.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA };'13: Proceedings of the Eighth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {255--264},
   year = {2013},
   doi = {},
   url = {http://www.sipta.org/isipta13/proceedings/papers/s025.pdf}
}
Download
Zaffalon, M., Miranda, E. (2013). Probability and time. Artificial Intelligence 198, pp. 1–51.

Probability and time

@ARTICLE{zaffalon2013a,
   title = {Probability and time},
   journal = {Artificial Intelligence},
   volume = {198},
   author = {Zaffalon, M. and Miranda, E.},
   pages = {1--51},
   year = {2013},
   doi = {10.1016/j.artint.2013.02.005},
   url = {}
}
Download
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2012

Antonucci, A. (2012). An interval-valued dissimilarity measure for belief functions based on credal semantics. In Denoeux, T., Masson, M.H. (Eds), Belief Functions: Theory and Applications, Advances in Intelligent and Soft Computing 164, Springer Berlin / Heidelberg, pp. 37–44.

An interval-valued dissimilarity measure for belief functions based on credal semantics

@INPROCEEDINGS{antonucci2012a,
   title = {An interval-valued dissimilarity measure for belief functions based on credal semantics},
   editor = {Denoeux, T. and Masson, M.H.},
   publisher = {Springer Berlin / Heidelberg},
   series = {Advances in Intelligent and Soft Computing},
   volume = {164},
   booktitle = {Belief Functions: Theory and Applications},
   author = {Antonucci, A.},
   pages = {37--44},
   year = {2012},
   doi = {10.1007/978-3-642-29461-7_4},
   url = {}
}
Download
Antonucci, A., Cattaneo, M.E.V.G., Corani, G. (2012). Likelihood-based robust classification with Bayesian networks. In Communications in Computer and Information Science, Advances in Computational Intelligence 299(5), Springer Berlin / Heidelberg, pp. 491–500.

Likelihood-based robust classification with Bayesian networks

@INPROCEEDINGS{antonucci2012b,
   title = {Likelihood-based robust classification with {B}ayesian networks},
   publisher = {Springer Berlin / Heidelberg},
   series = {Advances in Computational Intelligence},
   volume = {299},
   booktitle = {Communications in Computer and Information Science},
   author = {Antonucci, A. and Cattaneo, M.E.V.G. and Corani, G.},
   number = {5},
   pages = {491--500},
   year = {2012},
   doi = {10.1007/978-3-642-31718-7_51},
   url = {}
}
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Antonucci, A., Corani, G., Gabaglio, S. (2012). Active learning by the naive credal classifier. In Cano, A., Gomez-Olmedo, M., Nielsen, T. (Eds), Proc. of the 6th European Workshop on Probabilistic Graphical Models (PGM 2012), pp. 3–10.

Active learning by the naive credal classifier

@INPROCEEDINGS{antonucci2012c,
   title = {Active learning by the naive credal classifier},
   editor = {Cano, A. and Gomez-Olmedo, M. and Nielsen, T.},
   booktitle = {Proc. {o}f the 6th European Workshop on Probabilistic Graphical Models ({PGM} 2012)},
   author = {Antonucci, A. and Corani, G. and Gabaglio, S.},
   pages = {3--10},
   year = {2012},
   doi = {},
   url = {}
}
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Battistelli, G., Benavoli, A., Chisci, L. (2012). State estimation with remote sensors and intermittent transmissions. Systems & Control Letters 61(1), pp. 155–164.

State estimation with remote sensors and intermittent transmissions

@ARTICLE{benavoli2012d,
   title = {State estimation with remote sensors and intermittent transmissions},
   journal = {Systems & Control Letters},
   volume = {61},
   author = {Battistelli, G. and Benavoli, A. and Chisci, L.},
   number = {1},
   pages = {155--164},
   year = {2012},
   doi = {10.1016/j.sysconle.2011.10.005},
   url = {}
}
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Battistelli, G., Benavoli, A., Chisci, L. (2012). Data-driven communication for state estimation with sensor networks. Automatica 48(5), pp. 926–935.

Data-driven communication for state estimation with sensor networks

@ARTICLE{benavoli2012c,
   title = {Data-driven communication for state estimation with sensor networks},
   journal = {Automatica},
   volume = {48},
   author = {Battistelli, G. and Benavoli, A. and Chisci, L.},
   number = {5},
   pages = {926--935},
   year = {2012},
   doi = {10.1016/j.automatica.2012.02.028},
   url = {}
}
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Battistelli, G., Benavoli, A., Chisci, L. (2012). Data-driven strategies for selective data transmission in sensor networks. In CDC 2012, Proc. of the 51st Ieee Conference on Decision and Control, Maui, Usa, pp. 1–6.

Data-driven strategies for selective data transmission in sensor networks

@INPROCEEDINGS{benavoli2012f,
   title = {Data-driven strategies for selective data transmission in sensor networks},
   booktitle = {{CDC} 2012, Proc. {o}f the 51st Ieee Conference on Decision and Control, Maui, Usa},
   author = {Battistelli, G. and Benavoli, A. and Chisci, L.},
   pages = {1--6},
   year = {2012},
   doi = {},
   url = {}
}
Download
Benavoli, A. (2012). Belief function robustness in estimation. In Denoeux, T., Masson, M.-H. (Eds), Belief Functions: Theory and Applications, Advances in Intelligent and Soft Computing 164, Springer Berlin / Heidelberg, pp. 375–383.

Belief function robustness in estimation

@INCOLLECTION{benavoli2012a,
   title = {Belief function robustness in estimation},
   editor = {Denoeux, T. and Masson, M.-H.},
   publisher = {Springer Berlin / Heidelberg},
   series = {Advances in Intelligent and Soft Computing},
   volume = {164},
   booktitle = {Belief Functions: Theory and Applications},
   author = {Benavoli, A.},
   pages = {375--383},
   year = {2012},
   doi = {10.1007/978-3-642-29461-7_44},
   url = {}
}
Download
Benavoli, A., Noack, B. (2012). Pushing Kalman's idea to the extremes. In 2012 15th International Conference on Information Fusion, pp. 1202–1209.

Pushing Kalman's idea to the extremes

@INPROCEEDINGS{benavoli2012e,
   title = {Pushing {K}alman's idea to the extremes},
   booktitle = {2012 15th International Conference on Information Fusion},
   author = {Benavoli, A. and Noack, B.},
   pages = {1202--1209},
   year = {2012},
   doi = {},
   url = {https://ieeexplore.ieee.org/document/6289945}
}
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Benavoli, A., Zaffalon, M. (2012). A model of prior ignorance for inferences in the one-parameter exponential family. Journal of Statistical Planning and Inference 142(7), pp. 1960–1979.

A model of prior ignorance for inferences in the one-parameter exponential family

@ARTICLE{benavoli2012b,
   title = {A model of prior ignorance for inferences in the one-parameter exponential family},
   journal = {Journal of Statistical Planning and Inference},
   volume = {142},
   author = {Benavoli, A. and Zaffalon, M.},
   number = {7},
   pages = {1960--1979},
   year = {2012},
   doi = {10.1016/j.jspi.2012.01.023},
   url = {}
}
Download
Corani, G., Antonucci, A., De Rosa, R. (2012). Compression-based AODE classifiers. In De Raedt, L. et al. (Ed), Proc. 20th European Conference on Artificial Intelligence (ECAI 2012), pp. 264–269.

Compression-based AODE classifiers

@INPROCEEDINGS{corani2012d,
   title = {Compression-based {AODE} classifiers},
   editor = {De Raedt, L. et al. },
   booktitle = {Proc. 20th European Conference on Artificial Intelligence ({ECAI} 2012)},
   author = {Corani, G. and Antonucci, A. and De Rosa, R.},
   pages = {264--269},
   year = {2012},
   doi = {},
   url = {}
}
Download
Corani, G., Antonucci, A., Zaffalon, M. (2012). Bayesian networks with imprecise probabilities: theory and application to classification. In Holmes, D.E., Jain, L.C. (Eds), Data Mining: Foundations and Intelligent Paradigms, Intelligent Systems Reference Library 23, Springer, Berlin / Heidelberg, pp. 49–93.

Bayesian networks with imprecise probabilities: theory and application to classification

@INCOLLECTION{corani2012c,
   title = {Bayesian networks with imprecise probabilities: theory and application to classification},
   editor = {Holmes, D.E. and Jain, L.C.},
   publisher = {Springer, Berlin / Heidelberg},
   series = {Intelligent Systems Reference Library},
   volume = {23},
   booktitle = {Data Mining: Foundations and Intelligent Paradigms},
   author = {Corani, G. and Antonucci, A. and Zaffalon, M.},
   pages = {49--93},
   year = {2012},
   doi = {10.1007/978-3-642-23166-7_4},
   url = {}
}
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Corani, G., Magli, C., Giusti, A., Gianaroli, L., Gambardella, L. (2012). A Bayesian network model for predicting the outcome of in vitro fertilization. In Cano, A., Gomez-Olmedo, M., Nielsen, T. (Eds), Proc. of the 6th European Workshop on Probabilistic Graphical Models (PGM 2012), pp. 75–82.

A Bayesian network model for predicting the outcome of in vitro fertilization

@INPROCEEDINGS{corani2012e,
   title = {A {B}ayesian network model for predicting the outcome of in vitro fertilization},
   editor = {Cano, A. and Gomez-Olmedo, M. and Nielsen, T.},
   booktitle = {Proc. {o}f the 6th European Workshop on Probabilistic Graphical Models ({PGM} 2012)},
   author = {Corani, G. and Magli, C. and Giusti, A. and Gianaroli, L. and Gambardella, L.},
   pages = {75--82},
   year = {2012},
   doi = {},
   url = {}
}
Download
Magli, C., Corani, G., Giusti, A., Castelletti, E., Gambardella, L., Gianaroli, L. (2012). A prognostic model for multiple-embryo transfers. Human Reproduction (Supplement: Abstract book, Proc. Annual Meeting ESHRE 2012) 27(2), pp. ii162–ii205.

A prognostic model for multiple-embryo transfers

@ARTICLE{corani2012b,
   title = {A prognostic model for multiple-embryo transfers},
   journal = {Human Reproduction (Supplement: Abstract {b}ook, Proc. Annual Meeting {ESHRE} 2012)},
   volume = {27},
   author = {Magli, C. and Corani, G. and Giusti, A. and Castelletti, E. and Gambardella, L. and Gianaroli, L.},
   number = {2},
   pages = {ii162--ii205},
   year = {2012},
   doi = {10.1093/humrep/27.s2.77},
   url = {}
}
Download
Mauá, D.D., de Campos, C.P., Zaffalon, M. (2012). Solving limited memory influence diagrams. Journal of Artificial Intelligence Research 44, pp. 97–140.

Solving limited memory influence diagrams

@ARTICLE{maua2012a,
   title = {Solving limited memory influence diagrams},
   journal = {Journal of Artificial Intelligence Research},
   volume = {44},
   author = {Mau\'a, D.D. and de Campos, C.P. and Zaffalon, M.},
   pages = {97--140},
   year = {2012},
   doi = {},
   url = {http://www.jair.org/media/3625/live-3625-6282-jair.pdf}
}
Download
Mauá, D.D., de Campos, C.P., Zaffalon, M. (2012). Updating credal networks is approximable in polynomial time. International Journal of Approximate Reasoning 53(8), pp. 1183–1199.

Updating credal networks is approximable in polynomial time

@ARTICLE{maua2012d,
   title = {Updating credal networks is approximable in polynomial time},
   journal = {International Journal of Approximate Reasoning},
   volume = {53},
   author = {Mau\'a, D.D. and de Campos, C.P. and Zaffalon, M.},
   number = {8},
   pages = {1183--1199},
   year = {2012},
   doi = {10.1016/j.ijar.2012.06.014},
   url = {http://www.sciencedirect.com/science/article/pii/S0888613X12000904?v=s5}
}
Download
Mauá, D.D., de Campos, C.P. (2012). Anytime marginal map inference. In Proceedings of the 28th International Conference on Machine Learning (ICML 2012), pp. 1471–1478.

Anytime marginal map inference

@INPROCEEDINGS{maua2012b,
   title = {Anytime marginal map inference},
   booktitle = {Proceedings of the 28th International Conference on Machine Learning ({ICML} 2012)},
   author = {Mau\'a, D.D. and de Campos, C.P.},
   pages = {1471--1478},
   year = {2012},
   doi = {},
   url = {http://icml.cc/2012/papers/728.pdf}
}
Download
Mauá, D.D., de Campos, C.P., Zaffalon, M. (2012). The complexity of approximately solving influence diagrams. In Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence (UAI 2012), pp. 604–613.

The complexity of approximately solving influence diagrams

@INPROCEEDINGS{maua2012c,
   title = {The complexity of approximately solving influence diagrams},
   booktitle = {Proceedings of the 28th Conference on Uncertainty in Artificial Intelligence ({UAI} 2012)},
   author = {Mau\'a, D.D. and de Campos, C.P. and Zaffalon, M.},
   pages = {604--613},
   year = {2012},
   doi = {},
   url = {http://www.auai.org/uai2012/papers/166.pdf}
}
Download
Mignatti, A., Corani, G., Rizzoli, A.E. (2012). Credal model averaging: dealing robustly with model uncertainty on small data sets. In Proc. 6th International Congress on Environmental Modelling and Software (iEMSs 2012), pp. 163–170.

Credal model averaging: dealing robustly with model uncertainty on small data sets

@INCOLLECTION{corani2012a,
   title = {Credal model averaging: dealing robustly with model uncertainty on small data sets},
   booktitle = {Proc. 6th International Congress on Environmental Modelling and Software ({iEMSs} 2012)},
   author = {Mignatti, A. and Corani, G. and Rizzoli, A.E.},
   pages = {163--170},
   year = {2012},
   doi = {},
   url = {http://www.iemss.org/iemss2012/proceedings/A3_0707_Mignatti_et_al.pdf}
}
Download
Miranda, E., Zaffalon, M., de Cooman, G. (2012). Conglomerable natural extension. International Journal of Approximate Reasoning 53(8), pp. 1200–1227.

Conglomerable natural extension

@ARTICLE{zaffalon2012b,
   title = {Conglomerable natural extension},
   journal = {International Journal of Approximate Reasoning},
   volume = {53},
   author = {Miranda, E. and Zaffalon, M. and de Cooman, G.},
   number = {8},
   pages = {1200--1227},
   year = {2012},
   doi = {10.1016/j.ijar.2012.06.015},
   url = {}
}
Download
Zaffalon, M., Corani, G., Mauá, D.D. (2012). Evaluating credal classifiers by utility-discounted predictive accuracy. International Journal of Approximate Reasoning 53(8), pp. 1282–1301.

Evaluating credal classifiers by utility-discounted predictive accuracy

@ARTICLE{zaffalon2012c,
   title = {Evaluating credal classifiers by utility-discounted predictive accuracy},
   journal = {International Journal of Approximate Reasoning},
   volume = {53},
   author = {Zaffalon, M. and Corani, G. and Mau\'a, D.D.},
   number = {8},
   pages = {1282--1301},
   year = {2012},
   doi = {10.1016/j.ijar.2012.06.022},
   url = {}
}
Download
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2011

Antonucci, A. (2011). The imprecise noisy-or gate. In FUSION 2011: Proceedings of the 14th International Conference on Information Fusion, IEEE, pp. 709–715.

The imprecise noisy-or gate

@INPROCEEDINGS{antonucci2011c,
   title = {The imprecise noisy-or gate},
   publisher = {IEEE},
   booktitle = {{FUSION} 2011: Proceedings of the 14th International Conference on Information Fusion},
   author = {Antonucci, A.},
   pages = {709--715},
   year = {2011},
   doi = {},
   url = {}
}
Download
Antonucci, A., de Campos, C.P. (2011). Decision making by credal nets. In Proceedings of the International Conference on Intelligent Human-machine Systems and Cybernetics (IHMSC 2011) 1, IEEE, Hangzhou (China), pp. 201–204.

Decision making by credal nets

@INPROCEEDINGS{antonucci2011d,
   title = {Decision making by credal nets},
   publisher = {IEEE},
   address = {Hangzhou (China)},
   volume = {1},
   booktitle = {Proceedings of the International Conference on Intelligent Human-{m}achine Systems and Cybernetics ({IHMSC} 2011)},
   author = {Antonucci, A. and de Campos, C.P.},
   pages = {201--204},
   year = {2011},
   doi = {},
   url = {}
}
Download
Antonucci, A., Cattaneo, M., Corani, G. (2011). Likelihood-based naive credal classifier. In ISIPTA '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 21–30.

Likelihood-based naive credal classifier

@INPROCEEDINGS{antonucci2011a,
   title = {Likelihood-based naive credal classifier},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications},
   author = {Antonucci, A. and Cattaneo, M. and Corani, G.},
   pages = {21--30},
   year = {2011},
   doi = {},
   url = {http://www.sipta.org/isipta11/proceedings/papers/s032.pdf}
}
Download
Antonucci, A., de Rosa, R., Giusti, A. (2011). Action recognition by imprecise hidden Markov models. In Proceedings of the 2011 International Conference on Image Processing, Computer Vision and Pattern Recognition, IPCV 2011, CSREA Press, pp. 474–478.

Action recognition by imprecise hidden Markov models

@INPROCEEDINGS{antonucci2011b,
   title = {Action recognition by imprecise hidden {M}arkov models},
   publisher = {CSREA Press},
   booktitle = {Proceedings of the 2011 International Conference on Image Processing, Computer Vision and Pattern Recognition, {IPCV} 2011},
   author = {Antonucci, A. and de Rosa, R. and Giusti, A.},
   pages = {474--478},
   year = {2011},
   doi = {},
   url = {http://www.lidi.info.unlp.edu.ar/WorldComp2011-Mirror/IPC5150.pdf}
}
Download
Benavoli, A., Chisci, L. (2011). Robust stochastic control based on imprecise probabilities. In Proc. of the 18th IFAC World Congress, pp. 4606–4613.

Robust stochastic control based on imprecise probabilities

@INPROCEEDINGS{benavoli2011a,
   title = {Robust stochastic control based on imprecise probabilities},
   booktitle = {Proc. {o}f the 18th {IFAC} World Congress},
   author = {Benavoli, A. and Chisci, L.},
   pages = {4606--4613},
   year = {2011},
   doi = {},
   url = {}
}
Download
Benavoli, A., Ristic, B. (2011). Classification with imprecise likelihoods: a comparison of TBM, random set and imprecise probability approach. In Information Fusion (FUSION), 2011 Proc. of the 14th International Conference on, pp. 1–8.

Classification with imprecise likelihoods: a comparison of TBM, random set and imprecise probability approach

@INPROCEEDINGS{benavoli2011b,
   title = {Classification with imprecise likelihoods: a comparison of {TBM}, random set and imprecise probability approach},
   booktitle = {Information Fusion ({FUSION}), 2011 Proc. {o}f the 14th International Conference on},
   author = {Benavoli, A. and Ristic, B.},
   pages = {1--8},
   year = {2011},
   doi = {},
   url = {}
}
Download
Benavoli, A., Zaffalon, M. (2011). A discussion on learning and prior ignorance for sets of priors in the one-parameter exponential family. In ISIPTA '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications, Innsbruck (AU), pp. 1–10.

A discussion on learning and prior ignorance for sets of priors in the one-parameter exponential family

@INPROCEEDINGS{benavoli2011c,
   title = {A discussion on learning and prior ignorance for sets of priors in the one-parameter exponential family},
   address = {Innsbruck (AU)},
   booktitle = {{ISIPTA} '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications},
   author = {Benavoli, A. and Zaffalon, M.},
   pages = {1--10},
   year = {2011},
   doi = {},
   url = {http://www.sipta.org/isipta11/proceedings/papers/s027.pdf}
}
Download
Benavoli, A., Zaffalon, M., Miranda, E. (2011). Robust filtering through coherent lower previsions. Automatic Control, IEEE Transactions on 56(7), pp. 1567–1581.

Robust filtering through coherent lower previsions

@ARTICLE{benavoli2011d,
   title = {Robust filtering through coherent lower previsions},
   journal = {Automatic Control, {IEEE} Transactions on},
   volume = {56},
   author = {Benavoli, A. and Zaffalon, M. and Miranda, E.},
   number = {7},
   pages = {1567--1581},
   year = {2011},
   doi = {10.1109/TAC.2010.2090707},
   url = {}
}
Download
de Campos, C.P. (2011). New complexity results for MAP in Bayesian networks. In International Joint Conference on Artificial Intelligence (IJCAI), AAAI Press, pp. 2100–2106.

New complexity results for MAP in Bayesian networks

@INPROCEEDINGS{decampos2011c,
   title = {New complexity results for {MAP} in {B}ayesian networks},
   publisher = {AAAI Press},
   booktitle = {International Joint Conference on Artificial Intelligence ({IJCAI})},
   author = {de Campos, C.P.},
   pages = {2100--2106},
   year = {2011},
   doi = {},
   url = {http://ijcai.org/papers11/Papers/IJCAI11-351.pdf}
}
Download
de Campos, C.P., Benavoli, A. (2011). Inference with multinomial data: why to weaken the prior strength. In International Joint Conference on Artificial Intelligence (IJCAI), AAAI Press, pp. 2107–2112.

Inference with multinomial data: why to weaken the prior strength

@INPROCEEDINGS{decampos2011e,
   title = {Inference with multinomial data: why to weaken the prior strength},
   publisher = {AAAI Press},
   booktitle = {International Joint Conference on Artificial Intelligence ({IJCAI})},
   author = {de Campos, C.P. and Benavoli, A.},
   pages = {2107--2112},
   year = {2011},
   doi = {},
   url = {http://ijcai.org/papers11/Papers/IJCAI11-352.pdf}
}
Download
de Campos, C.P., Ji, Q. (2011). Efficient structure learning of Bayesian networks using constraints. Journal of Machine Learning Research 12, pp. 663–689.

Efficient structure learning of Bayesian networks using constraints

@ARTICLE{decampos2011a,
   title = {Efficient structure learning of {B}ayesian networks using constraints},
   journal = {Journal of Machine Learning Research},
   volume = {12},
   author = {de Campos, C.P. and Ji, Q.},
   pages = {663--689},
   year = {2011},
   doi = {},
   url = {http://jmlr.csail.mit.edu/papers/volume12/decampos11a/decampos11a.pdf}
}
Download
de Campos, C., Ji, Q. (2011). Bayesian networks and the imprecise Dirichlet model applied to recognition problems. In Liu, W. (Ed), Symbolic and Quantitative Approaches to Reasoning With Uncertainty, Lecture Notes in Computer Science 6717, Springer, Berlin / Heidelberg, pp. 158–169.

Bayesian networks and the imprecise Dirichlet model applied to recognition problems

@INPROCEEDINGS{decampos2011f,
   title = {Bayesian networks and the imprecise {D}irichlet model applied to recognition problems},
   editor = {Liu, W.},
   publisher = {Springer, Berlin / Heidelberg},
   series = {Lecture Notes in Computer Science},
   volume = {6717},
   booktitle = {Symbolic and Quantitative Approaches to Reasoning With Uncertainty},
   author = {de Campos, C. and Ji, Q.},
   pages = {158--169},
   year = {2011},
   doi = {10.1007/978-3-642-22152-1_14},
   url = {}
}
Download
de Cooman, G., Miranda, E., Zaffalon, M. (2011). Independent natural extension. Artificial Intelligence 175, pp. 1911–1950.

Independent natural extension

@ARTICLE{zaffalon2011a,
   title = {Independent natural extension},
   journal = {Artificial Intelligence},
   volume = {175},
   author = {de Cooman, G. and Miranda, E. and Zaffalon, M.},
   pages = {1911--1950},
   year = {2011},
   doi = {10.1016/j.artint.2011.06.001},
   url = {}
}
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de Lalla, C., Rinaldi, A., Montagna, D., Azzimonti, L., Bernardo, M.E., Sangalli, L.M., Paganoni, A.M., Maccario, R., Cesare-Merlone, A.D., Zecca, M., Locatelli, F., Dellabona, P., Casorati, G. (2011). Invariant Natural Killer T-cell reconstitution in pediatric leukemia patients given HLA-haploidentical stem cell transplantation defines distinct CD4+ and CD4- subset dynamics and associates with the remission state. The Journal of Immunology 186(7), pp. 4490–4499.

Invariant Natural Killer T-cell reconstitution in pediatric leukemia patients given HLA-haploidentical stem cell transplantation defines distinct CD4+ and CD4- subset dynamics and associates with the remission state

@ARTICLE{azzimonti2011a,
   title = {Invariant {N}atural {K}iller {T}-cell reconstitution in pediatric leukemia patients given {HLA}-haploidentical stem cell transplantation defines distinct {CD4+} and {CD4}- subset dynamics and associates with the remission state},
   journal = {The Journal of Immunology},
   volume = {186},
   author = {de Lalla, C. and Rinaldi, A. and Montagna, D. and Azzimonti, L. and Bernardo, M.E. and Sangalli, L.M. and Paganoni, A.M. and Maccario, R. and Cesare-Merlone, A.D. and Zecca, M. and Locatelli, F. and Dellabona, P. and Casorati, G.},
   number = {7},
   pages = {4490--4499},
   year = {2011},
   doi = {10.4049/jimmunol.1003748},
   url = {}
}
Download
Mauá, D.D., de Campos, C.P. (2011). Solving decision problems with limited information. In Shawe-Taylor, J., Zemel, R.S., Bartlett, P., Pereira, F.C.N., Weinberger, K.Q. (Eds), Advances in Neural Information Processing Systems 24 (NIPS 2011), pp. 603–611.

Solving decision problems with limited information

@INCOLLECTION{maua2011a,
   title = {Solving decision problems with limited information},
   editor = {Shawe-Taylor, J. and Zemel, R.S. and Bartlett, P. and Pereira, F.C.N. and Weinberger, K.Q.},
   booktitle = {Advances in Neural Information Processing Systems 24 ({NIPS} 2011)},
   author = {Mau\'a, D.D. and de Campos, C.P.},
   pages = {603--611},
   year = {2011},
   doi = {},
   url = {http://books.nips.cc/papers/files/nips24/NIPS2011_0422.pdf}
}
Download
Mauá, D.D., de Campos, C.P., Zaffalon, M. (2011). A fully polynomial time approximation scheme for updating credal networks of bounded treewidth and number of variable states. In Coolen, F., de Cooman, G., Fetz, T., Oberguggenberger, M. (Eds), ISIPTA '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications, SIPTA, Innsbruck, Austria, pp. 277–286.

A fully polynomial time approximation scheme for updating credal networks of bounded treewidth and number of variable states

@INPROCEEDINGS{maua2011b,
   title = {A fully polynomial time approximation scheme for updating credal networks of bounded treewidth and number of variable states},
   editor = {Coolen, F. and de Cooman, G. and Fetz, T. and Oberguggenberger, M.},
   publisher = {SIPTA},
   address = {Innsbruck, Austria},
   booktitle = {{ISIPTA} '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications},
   author = {Mau\'a, D.D. and de Campos, C.P. and Zaffalon, M.},
   pages = {277--286},
   year = {2011},
   doi = {},
   url = {http://leo.ugr.es/sipta/isipta11/proceedings/papers/s035.pdf}
}
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Miranda, E., Zaffalon, M., de Cooman, G. (2011). Conglomerable natural extension. In Coolen, F., de Cooman, G., Fetz, T., Oberguggenberger, M. (Eds), ISIPTA '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 287–296.

Conglomerable natural extension

@INPROCEEDINGS{zaffalon2011c,
   title = {Conglomerable natural extension},
   editor = {Coolen, F. and de Cooman, G. and Fetz, T. and Oberguggenberger, M.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications},
   author = {Miranda, E. and Zaffalon, M. and de Cooman, G.},
   pages = {287--296},
   year = {2011},
   doi = {},
   url = {http://www.sipta.org/isipta11/proceedings/papers/s030.pdf}
}
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Rinaldi, A., Mian, M., Chigrinova, E., Arcaini, L., Bhagat, G., Novak, U., Rancoita, P.M.V., Campos, C.P.D., Forconi, F., Gascoyne, R.D., Facchetti, F., Ponzoni, M., Govi, S., Ferreri, A.J.M., Mollejo, M., Piris, M.A., Baldini, L., Soulier, J., Thieblemont, C., Canzonieri, V., Gattei, V., Marasca, R., Franceschetti, S., Gaidano, G., Tucci, A., Uccella, S., Tibiletti, M.G., Dirnhofer, S., Tripodo, C., Doglioni, C., Favera, R.D., Cavalli, F., Zucca, E., Kwee, I., Bertoni, F. (2011). Genome-wide DNA profiling of marginal zone lymphomas identifies subtype-specific lesions with an impact on the clinical outcome. Blood 117(5), pp. 1595–1604.

Genome-wide DNA profiling of marginal zone lymphomas identifies subtype-specific lesions with an impact on the clinical outcome

@ARTICLE{decampos2011b,
   title = {Genome-wide {DNA} profiling of marginal zone lymphomas identifies subtype-specific lesions with an impact on the clinical outcome},
   journal = {Blood},
   publisher = {The American Society of Hematology},
   volume = {117},
   author = {Rinaldi, A. and Mian, M. and Chigrinova, E. and Arcaini, L. and Bhagat, G. and Novak, U. and Rancoita, P.M.V. and Campos, C.P.D. and Forconi, F. and Gascoyne, R.D. and Facchetti, F. and Ponzoni, M. and Govi, S. and Ferreri, A.J.M. and Mollejo, M. and Piris, M.A. and Baldini, L. and Soulier, J. and Thieblemont, C. and Canzonieri, V. and Gattei, V. and Marasca, R. and Franceschetti, S. and Gaidano, G. and Tucci, A. and Uccella, S. and Tibiletti, M.G. and Dirnhofer, S. and Tripodo, C. and Doglioni, C. and Favera, R.D. and Cavalli, F. and Zucca, E. and Kwee, I. and Bertoni, F.},
   number = {5},
   pages = {1595--1604},
   year = {2011},
   doi = {10.1182/blood-2010-01-264275},
   url = {http://bloodjournal.hematologylibrary.org/content/117/5/1595.full.pdf+html}
}
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Zaffalon, M., Corani, G., Mauá, D.D. (2011). Utility-based accuracy measures to empirically evaluate credal classifiers. In Coolen, F., de Cooman, G., Fetz, T., Oberguggenberger, M. (Eds), ISIPTA '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 401–410.

Utility-based accuracy measures to empirically evaluate credal classifiers

@INPROCEEDINGS{zaffalon2011b,
   title = {Utility-based accuracy measures to empirically evaluate credal classifiers},
   editor = {Coolen, F. and de Cooman, G. and Fetz, T. and Oberguggenberger, M.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '11: Proceedings of the Seventh International Symposium on Imprecise Probability: Theories and Applications},
   author = {Zaffalon, M. and Corani, G. and Mau\'a, D.D.},
   pages = {401--410},
   year = {2011},
   doi = {},
   url = {http://www.sipta.org/isipta11/proceedings/papers/s016.pdf}
}
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2010

Antonucci, A., Cuzzolin, F. (2010). Credal sets approximation by lower probabilities: application to credal networks. In Hüllermeier, E., Kruse, R., Hoffmann, F. (Eds), Computational Intelligence for Knowledge-based Systems Design, 13th International Conference on Information Processing and Management of Uncertainty, IPMU 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings, Lecture Notes in Computer Science 6178, Springer, pp. 716–725.

Credal sets approximation by lower probabilities: application to credal networks

@INPROCEEDINGS{antonucci2010a,
   title = {Credal sets approximation by lower probabilities: application to credal networks},
   editor = {H\"ullermeier, E. and Kruse, R. and Hoffmann, F.},
   publisher = {Springer},
   series = {Lecture Notes in Computer Science},
   volume = {6178},
   booktitle = {Computational Intelligence for Knowledge-{b}ased Systems Design, 13th International Conference on Information Processing and Management of Uncertainty, {IPMU} 2010, Dortmund, Germany, June 28 - July 2, 2010. Proceedings},
   author = {Antonucci, A. and Cuzzolin, F.},
   pages = {716--725},
   year = {2010},
   doi = {10.1007/978-3-642-14049-5_73},
   url = {}
}
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Antonucci, A., Yi, S., de Campos, C.P., Zaffalon, M. (2010). Generalized loopy 2U: a new algorithm for approximate inference in credal networks. International Journal of Approximate Reasoning 55(5), pp. 474–484.

Generalized loopy 2U: a new algorithm for approximate inference in credal networks

@ARTICLE{antonucci2010c,
   title = {Generalized loopy {2U}: a new algorithm for approximate inference in credal networks},
   journal = {International Journal of Approximate Reasoning},
   volume = {55},
   author = {Antonucci, A. and Yi, S. and de Campos, C.P. and Zaffalon, M.},
   number = {5},
   pages = {474--484},
   year = {2010},
   doi = {10.1016/j.ijar.2010.01.007},
   url = {}
}
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Benavoli, A., Antonucci, A. (2010). Aggregating imprecise probabilistic knowledge: application to Zadeh's paradox and sensor networks. Int. Journal of Approximate Reasoning 51(9), pp. 1014–1028.

Aggregating imprecise probabilistic knowledge: application to Zadeh's paradox and sensor networks

@ARTICLE{benavoli2010a,
   title = {Aggregating imprecise probabilistic knowledge: application to {Z}adeh's paradox and sensor networks},
   journal = {Int. Journal of Approximate Reasoning},
   volume = {51},
   author = {Benavoli, A. and Antonucci, A.},
   number = {9},
   pages = {1014--1028},
   year = {2010},
   doi = {10.1016/j.ijar.2010.08.010},
   url = {}
}
Download
de Campos, C.P., Ji, Q. (2010). Properties of Bayesian Dirichlet scores to learn Bayesian network structures. In AAAI Conference on Artificial Intelligence, AAAI Press, pp. 431–436.

Properties of Bayesian Dirichlet scores to learn Bayesian network structures

@INPROCEEDINGS{decampos2010c,
   title = {Properties of {B}ayesian {D}irichlet scores to learn {B}ayesian network structures},
   publisher = {AAAI Press},
   booktitle = {{AAAI} Conference on Artificial Intelligence},
   author = {de Campos, C.P. and Ji, Q.},
   pages = {431--436},
   year = {2010},
   doi = {},
   url = {http://www.aaai.org/ocs/index.php/AAAI/AAAI10/paper/view/1704/2013}
}
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de Campos, C.P., Zeng, Z., Ji, Q. (2010). An improved structural EM to learn dynamic Bayesian nets. In 20th International Conference on Pattern Recognition (ICPR), pp. 601–604.

An improved structural EM to learn dynamic Bayesian nets

@INPROCEEDINGS{decampos2010d,
   title = {An improved structural {EM} to learn dynamic {B}ayesian nets},
   booktitle = {20th International Conference on Pattern Recognition ({ICPR})},
   author = {de Campos, C.P. and Zeng, Z. and Ji, Q.},
   pages = {601--604},
   year = {2010},
   doi = {10.1109/ICPR.2010.152},
   url = {}
}
Download
de Cooman, G., Hermans, F., Antonucci, A., Zaffalon, M. (2010). Epistemic irrelevance in credal nets: the case of imprecise markov trees. International Journal of Approximate Reasoning 51(9), pp. 1029–1052.

Epistemic irrelevance in credal nets: the case of imprecise markov trees

@ARTICLE{antonucci2010b,
   title = {Epistemic irrelevance in credal nets: the case of imprecise markov trees},
   journal = {International Journal of Approximate Reasoning},
   volume = {51},
   author = {de Cooman, G. and Hermans, F. and Antonucci, A. and Zaffalon, M.},
   number = {9},
   pages = {1029--1052},
   year = {2010},
   doi = {10.1016/j.ijar.2010.08.011},
   url = {}
}
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de Cooman, G., Miranda, E., Zaffalon, M. (2010). Factorisation properties of the strong product. In Borgelt, C., González Rodrìguez, G., Trutschnig, W., Asunción Lubiano, M., Gil, M.A., Grzegorzewski, P., Hryniewicz, O. (Eds), Combining Soft Computing and Statistical Methods in Data Analysis, Advances in Intelligent and Soft Computing 77, Springer, pp. 139–147.

Factorisation properties of the strong product

@INPROCEEDINGS{zaffalon2010c,
   title = {Factorisation properties of the strong product},
   editor = {Borgelt, C. and Gonz\'alez Rodr\`iguez, G. and Trutschnig, W. and Asunci\'on Lubiano, M. and Gil, M.A. and Grzegorzewski, P. and Hryniewicz, O.},
   publisher = {Springer},
   series = {Advances in Intelligent and Soft Computing},
   volume = {77},
   booktitle = {Combining Soft Computing and Statistical Methods in Data Analysis},
   author = {de Cooman, G. and Miranda, E. and Zaffalon, M.},
   pages = {139--147},
   year = {2010},
   doi = {10.1007/978-3-642-14746-3_18},
   url = {}
}
Download
de Cooman, G., Miranda, E., Zaffalon, M. (2010). Independent natural extension. In Hüllermeier, E., Kruse, R., Hoffmann, F. (Eds), Computational Intelligence for Knowledge-based Systems Design, Lecture Notes in Computer Science 6178, Springer, pp. 737–746.

Independent natural extension

@INPROCEEDINGS{zaffalon2010b,
   title = {Independent natural extension},
   editor = {H\"ullermeier, E. and Kruse, R. and Hoffmann, F.},
   publisher = {Springer},
   series = {Lecture Notes in Computer Science},
   volume = {6178},
   booktitle = {Computational Intelligence for Knowledge-{b}ased Systems Design},
   author = {de Cooman, G. and Miranda, E. and Zaffalon, M.},
   pages = {737--746},
   year = {2010},
   doi = {10.1007/978-3-642-14049-5_75},
   url = {}
}
Download
Corani, G., Benavoli, A. (2010). Restricting the IDM for classification. In Hullermeier, E., Kruse, R., Hoffmann, F. (Eds), Information Processing and Management of Uncertainty in Knowledge-based Systems. Theory and Methods, Communications in Computer and Information Science 80, Springer, Berlin / Heidelberg, pp. 328–337.

Restricting the IDM for classification

@INCOLLECTION{corani2010a,
   title = {Restricting the {IDM} for classification},
   editor = {Hullermeier, E. and Kruse, R. and Hoffmann, F.},
   publisher = {Springer, Berlin / Heidelberg},
   series = {Communications in Computer and Information Science},
   volume = {80},
   booktitle = {Information Processing and Management of Uncertainty in Knowledge-{b}ased Systems. Theory and Methods},
   author = {Corani, G. and Benavoli, A.},
   pages = {328--337},
   year = {2010},
   doi = {10.1007/978-3-642-14055-6_34},
   url = {}
}
Download
Corani, G., de Campos, C.P. (2010). A tree augmented classifier based on extreme imprecise Dirichlet model. International Journal of Approximate Reasoning 51(9), pp. 1053–1068.

A tree augmented classifier based on extreme imprecise Dirichlet model

@ARTICLE{Corani2010b,
   title = {A tree augmented classifier based on extreme imprecise {D}irichlet model},
   journal = {International Journal of Approximate Reasoning},
   volume = {51},
   author = {Corani, G. and de Campos, C.P.},
   number = {9},
   pages = {1053--1068},
   year = {2010},
   doi = {10.1016/j.ijar.2010.08.007},
   url = {}
}
Download
Corani, G., Giusti, A., Migliore, D., Schmidhuber, J. (2010). Robust texture recognition using credal classifiers. In Labrosse, F., Zwiggelaar, R., Liu, Y., Tiddeman, B. (Eds), Proceedings of the British Machine Vision Conference, BMVA Press, pp. 78.1–78.10.

Robust texture recognition using credal classifiers

@INPROCEEDINGS{corani2010c,
   title = {Robust texture recognition using credal classifiers},
   editor = {Labrosse, F. and Zwiggelaar, R. and Liu, Y. and Tiddeman, B.},
   publisher = {BMVA Press},
   booktitle = {Proceedings of the British Machine Vision Conference},
   author = {Corani, G. and Giusti, A. and Migliore, D. and Schmidhuber, J.},
   pages = {78.1--78.10},
   year = {2010},
   doi = {10.5244/C.24.78},
   url = {}
}
Download
Giusti, A., Corani, G., Gambardella, L., Magli, C., Gianaroli, L. (2010). 3D localization of pronuclei of human zygotes using textures from multiple focal planes. In Jiang, T., Navab, N., Pluim, J., Viergever, M. (Eds), Medical Image Computing and Computer-assisted Intervention - MICCAI 2010, Lecture Notes in Computer Science 6362, Springer, Berlin / Heidelberg, pp. 488–495.

3D localization of pronuclei of human zygotes using textures from multiple focal planes

@INCOLLECTION{corani2010d,
   title = {{3D} localization of pronuclei of human zygotes using textures from multiple focal planes},
   editor = {Jiang, T. and Navab, N. and Pluim, J. and Viergever, M.},
   publisher = {Springer, Berlin / Heidelberg},
   series = {Lecture Notes in Computer Science},
   volume = {6362},
   booktitle = {Medical Image Computing and Computer-{a}ssisted Intervention - {MICCAI} 2010},
   author = {Giusti, A. and Corani, G. and Gambardella, L. and Magli, C. and Gianaroli, L.},
   pages = {488--495},
   year = {2010},
   doi = {10.1007/978-3-642-15745-5_60},
   url = {}
}
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Miranda, E., Zaffalon, M. (2010). Notes on desirability and conditional lower previsions. Annals of Mathematics and Artificial Intelligence 60(3–4), pp. 251–309.

Notes on desirability and conditional lower previsions

@ARTICLE{zaffalon2010e,
   title = {Notes on desirability and conditional lower previsions},
   journal = {Annals of Mathematics and Artificial Intelligence},
   volume = {60},
   author = {Miranda, E. and Zaffalon, M.},
   number = {3--4},
   pages = {251--309},
   year = {2010},
   doi = {10.1007/s10472-011-9231-4},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2010). Conditional models: coherence and inference through sequences of joint mass functions. Journal of Statistical Planning and Inference 140(7), pp. 1805–1833.

Conditional models: coherence and inference through sequences of joint mass functions

@ARTICLE{zaffalon2010a,
   title = {Conditional models: coherence and inference through sequences of joint mass functions},
   journal = {Journal of Statistical Planning and Inference},
   volume = {140},
   author = {Miranda, E. and Zaffalon, M.},
   number = {7},
   pages = {1805--1833},
   year = {2010},
   doi = {10.1016/j.jspi.2010.01.005},
   url = {}
}
Download
Pelessoni, R., Vicig, P., Zaffalon, M. (2010). Inference and risk measurement with the pari-mutuel model. International Journal of Approximate Reasoning 51(9), pp. 1145–1158.

Inference and risk measurement with the pari-mutuel model

@ARTICLE{zaffalon2010d,
   title = {Inference and risk measurement with the pari-mutuel model},
   journal = {International Journal of Approximate Reasoning},
   volume = {51},
   author = {Pelessoni, R. and Vicig, P. and Zaffalon, M.},
   number = {9},
   pages = {1145--1158},
   year = {2010},
   doi = {10.1016/j.ijar.2010.08.005},
   url = {}
}
Download
Piatti, A., Antonucci, A., Zaffalon, M. (2010). Building knowledge-based expert systems by credal networks: a tutorial. In Baswell, A.R. (Ed), Advances in Mathematics Research 11, Nova Science Publishers, New York.

Building knowledge-based expert systems by credal networks: a tutorial

@INBOOK{antonucci2010d,
   title = {Building knowledge-based expert systems by credal networks: a tutorial},
   editor = {Baswell, A.R.},
   publisher = {Nova Science Publishers},
   address = {New York},
   volume = {11},
   booktitle = {Advances in Mathematics Research},
   author = {Piatti, A. and Antonucci, A. and Zaffalon, M.},
   year = {2010},
   chapter = {2},
   doi = {},
   url = {}
}
Download
Scandurra, M., Mian, M., Greiner, T.C., Rancoita, P.M.V., De Campos, C.P., Chan, W.C., Vose, J.M., Chigrinova, E., Inghirami, G., Chiappella, A., Baldini, L., Ponzoni, M., Ferreri, A.J.M., Franceschetti, S., Gaidano, G., Montes-Moreno, S., Piris, M.A., Facchetti, F., Tucci, A., Nomdedeu, J.F., Lazure, T., Lambotte, O., Uccella, S., Pinotti, G., Pruneri, G., Martinelli, G., Young, K.H., Tibiletti, M.G., Rinaldi, A., Zucca, E., Kwee, I., Bertoni, F. (2010). Genomic lesions associated with a different clinical outcome in diffuse large B-Cell lymphoma treated with R-CHOP-21. British Journal of Haematology 151(3), pp. 221–231.

Genomic lesions associated with a different clinical outcome in diffuse large B-Cell lymphoma treated with R-CHOP-21

@ARTICLE{decampos2010a,
   title = {Genomic lesions associated with a different clinical outcome in diffuse large {B}-{C}ell lymphoma treated with {R}-{CHOP}-21},
   journal = {British Journal of Haematology},
   publisher = {Blackwell Publishing Ltd},
   volume = {151},
   author = {Scandurra, M. and Mian, M. and Greiner, T.C. and Rancoita, P.M.V. and De Campos, C.P. and Chan, W.C. and Vose, J.M. and Chigrinova, E. and Inghirami, G. and Chiappella, A. and Baldini, L. and Ponzoni, M. and Ferreri, A.J.M. and Franceschetti, S. and Gaidano, G. and Montes-Moreno, S. and Piris, M.A. and Facchetti, F. and Tucci, A. and Nomdedeu, J.F. and Lazure, T. and Lambotte, O. and Uccella, S. and Pinotti, G. and Pruneri, G. and Martinelli, G. and Young, K.H. and Tibiletti, M.G. and Rinaldi, A. and Zucca, E. and Kwee, I. and Bertoni, F.},
   number = {3},
   pages = {221--231},
   year = {2010},
   doi = {10.1111/j.1365-2141.2010.08326.x},
   url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2141.2010.08326.x/pdf}
}
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2009

Antonucci, A., Benavoli, A., Zaffalon, M., de Cooman, G., Hermans, F. (2009). Multiple model tracking by imprecise Markov trees. In FUSION 2009: Proceedings of the 12th International Conference on Information Fusion, IEEE.

Multiple model tracking by imprecise Markov trees

@INPROCEEDINGS{antonucci2009e,
   title = {Multiple model tracking by imprecise {M}arkov trees},
   publisher = {IEEE},
   booktitle = {{FUSION} 2009: Proceedings of the 12th International Conference on Information Fusion},
   author = {Antonucci, A. and Benavoli, A. and Zaffalon, M. and de Cooman, G. and Hermans, F.},
   year = {2009},
   doi = {},
   url = {http://isif.org/fusion/proceedings/fusion09CD/data/papers/0478.pdf}
}
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Antonucci, A., Brühlmann, R., Piatti, A., Zaffalon, M. (2009). Credal networks for military identification problems. International Journal of Approximate Reasoning 50(2), pp. 666–679.

Credal networks for military identification problems

@ARTICLE{antonucci2009a,
   title = {Credal networks for military identification problems},
   journal = {International Journal of Approximate Reasoning},
   volume = {50},
   author = {Antonucci, A. and Br\"uhlmann, R. and Piatti, A. and Zaffalon, M.},
   number = {2},
   pages = {666--679},
   year = {2009},
   doi = {10.1016/j.ijar.2009.01.005},
   url = {}
}
Download
Antonucci, A., Piatti, A. (2009). Modeling unreliable observations in Bayesian networks by credal networks. In Godo, L., Pugliese, A. (Eds), Scalable Uncertainty Management, Third International Conference, SUM 2009, Washington, DC, USA, September 28–30, 2009. Proceedings, Lecture Notes in Computer Science 5785, Springer, pp. 28–39.

Modeling unreliable observations in Bayesian networks by credal networks

@INPROCEEDINGS{antonucci2009g,
   title = {Modeling unreliable observations in {B}ayesian networks by credal networks},
   editor = {Godo, L. and Pugliese, A.},
   publisher = {Springer},
   series = {Lecture Notes in Computer Science},
   volume = {5785},
   booktitle = {Scalable Uncertainty Management, Third International Conference, {SUM} 2009, Washington, {DC}, {USA}, September 28–30, 2009. Proceedings},
   author = {Antonucci, A. and Piatti, A.},
   pages = {28--39},
   year = {2009},
   doi = {10.1007/978-3-642-04388-8_4},
   url = {}
}
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Benavoli, A., Antonucci, A. (2009). Aggregating imprecise probabilistic knowledge. In ISIPTA '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications, Durham (UK), pp. 31–41.

Aggregating imprecise probabilistic knowledge

@INPROCEEDINGS{benavoli2009c,
   title = {Aggregating imprecise probabilistic knowledge},
   address = {Durham (UK)},
   booktitle = {{ISIPTA} '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Benavoli, A. and Antonucci, A.},
   pages = {31--41},
   year = {2009},
   doi = {},
   url = {http://www.sipta.org/isipta09/proceedings/papers/s043.pdf}
}
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Benavoli, A., de Campos, C.P. (2009). Inference from multinomial data based on a MLE-dominance criterion. In Proc. on European Conf. on Symbolic and Quantitative Approaches to Reasoning and Uncertainty (ECSQARU), Springer, Berlin / Heidelberg, Verona (IT), pp. 22–33.

Inference from multinomial data based on a MLE-dominance criterion

@INPROCEEDINGS{benavoli2009b,
   title = {Inference from multinomial data based on a {MLE}-dominance criterion},
   publisher = {Springer, Berlin / Heidelberg},
   address = {Verona (IT)},
   booktitle = {Proc. {o}n European Conf. {o}n Symbolic and Quantitative Approaches to Reasoning and Uncertainty ({ECSQARU})},
   author = {Benavoli, A. and de Campos, C.P.},
   pages = {22--33},
   year = {2009},
   doi = {10.1007/978-3-642-02906-6_4},
   url = {}
}
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Benavoli, A., Ristic, B., Farina, A., Oxenham, M., Chisci, L. (2009). An application of evidential networks to threat assessment. Aerospace and Electronic Systems, IEEE Transactions on 45(2), pp. 620–639.

An application of evidential networks to threat assessment

@ARTICLE{benavoli2009d,
   title = {An application of evidential networks to threat assessment},
   journal = {Aerospace and Electronic Systems, {IEEE} Transactions on},
   volume = {45},
   author = {Benavoli, A. and Ristic, B. and Farina, A. and Oxenham, M. and Chisci, L.},
   number = {2},
   pages = {620--639},
   year = {2009},
   doi = {10.1109/TAES.2009.5089545},
   url = {}
}
Download
Benavoli, A., Zaffalon, M., Miranda, E. (2009). Reliable hidden Markov model filtering through coherent lower previsions. In Information Fusion, 2009. FUSION '09. 12th International Conference on, Seattle (USA), pp. 1743–1750.

Reliable hidden Markov model filtering through coherent lower previsions

@INPROCEEDINGS{benavoli2009a,
   title = {Reliable hidden {M}arkov model filtering through coherent lower previsions},
   address = {Seattle (USA)},
   booktitle = {Information Fusion, 2009. {FUSION} '09. 12th International Conference on},
   author = {Benavoli, A. and Zaffalon, M. and Miranda, E.},
   pages = {1743--1750},
   year = {2009},
   doi = {},
   url = {http://isif.org/fusion/proceedings/fusion09CD/data/papers/0345.pdf}
}
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de Campos, C.P., Zeng, Z., Ji, Q. (2009). Structure learning of Bayesian networks using constraints. In International Conference on Machine Learning (ICML) 382, ACM, pp. 113–120.

Structure learning of Bayesian networks using constraints

@INPROCEEDINGS{decampos2009e,
   title = {Structure learning of {B}ayesian networks using constraints},
   publisher = {ACM},
   volume = {382},
   booktitle = {International Conference on Machine Learning ({ICML})},
   author = {de Campos, C.P. and Zeng, Z. and Ji, Q.},
   pages = {113--120},
   year = {2009},
   doi = {10.1145/1553374.1553389},
   url = {}
}
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de Cooman, G., Hermans, F., Antonucci, A., Zaffalon, M. (2009). Epistemic irrelevance in credal networks: the case of imprecise Markov trees. In Augustin, T., Coolen, F., Moral, S., Troffaes, M.C.M. (Eds), ISIPTA '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 149–158.

Epistemic irrelevance in credal networks: the case of imprecise Markov trees

@INPROCEEDINGS{antonucci2009c,
   title = {Epistemic irrelevance in credal networks: the case of imprecise {M}arkov trees},
   editor = {Augustin, T. and Coolen, F. and Moral, S. and Troffaes, M.C.M.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications},
   author = {de Cooman, G. and Hermans, F. and Antonucci, A. and Zaffalon, M.},
   pages = {149--158},
   year = {2009},
   doi = {},
   url = {http://www.sipta.org/isipta09/proceedings/papers/s053.pdf}
}
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Corani, G., Campos, C., Yi, S. (2009). A tree augmented classifier based on extreme imprecise Dirichlet model. In Augustin, T., Coolen, F.P.A., Moral, S., Troffaes, M.C.M. (Eds), ISIPTA '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, Durham, UK, pp. 89–98.

A tree augmented classifier based on extreme imprecise Dirichlet model

@INPROCEEDINGS{corani2009c,
   title = {A tree augmented classifier based on extreme imprecise {D}irichlet model},
   editor = {Augustin, T. and Coolen, F.P.A. and Moral, S. and Troffaes, M.C.M.},
   publisher = {SIPTA},
   address = {Durham, UK},
   booktitle = {{ISIPTA} '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Corani, G. and Campos, C. and Yi, S.},
   pages = {89--98},
   year = {2009},
   doi = {},
   url = {http://www.sipta.org/isipta09/proceedings/papers/s060.pdf}
}
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Corani, G., Rizzoli, A.E., Salvetti, A., Zaffalon, M. (2009). Reproducing human decisions in reservoir management: the case of lake lugano. In Information Technologies in Environmental Engineering, Springer, Berlin / Heidelberg, pp. 252–263.

Reproducing human decisions in reservoir management: the case of lake lugano

@INCOLLECTION{corani2009a,
   title = {Reproducing human decisions in reservoir management: the case of lake lugano},
   publisher = {Springer, Berlin / Heidelberg},
   booktitle = {Information Technologies in Environmental Engineering},
   author = {Corani, G. and Rizzoli, A.E. and Salvetti, A. and Zaffalon, M.},
   pages = {252--263},
   year = {2009},
   doi = {10.1007/978-3-540-88351-7_19},
   url = {}
}
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Corani, G., Zaffalon, M. (2009). Lazy naive credal classifier. In Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery From Uncertain Data, U '09, ACM, New York, NY, USA, pp. 30–37.

Lazy naive credal classifier

@INPROCEEDINGS{corani2009b,
   title = {Lazy naive credal classifier},
   publisher = {ACM},
   address = {New York, NY, USA},
   series = {U '09},
   booktitle = {Proceedings of the 1st {ACM} {SIGKDD} Workshop on Knowledge Discovery From Uncertain Data},
   author = {Corani, G. and Zaffalon, M.},
   pages = {30--37},
   year = {2009},
   doi = {10.1145/1610555.1610560},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2009). Coherence graphs. Artificial Intelligence 173, pp. 104–144.

Coherence graphs

@ARTICLE{zaffalon2009b,
   title = {Coherence graphs},
   journal = {Artificial Intelligence},
   volume = {173},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {104--144},
   year = {2009},
   doi = {10.1016/j.artint.2008.09.001},
   url = {}
}
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Miranda, E., Zaffalon, M. (2009). Natural extension as a limit of regular extensions. In Augustin, T., Coolen, F., Troffaes, M.C.M., Moral, S. (Eds), ISIPTA '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 327–336.

Natural extension as a limit of regular extensions

@INPROCEEDINGS{zaffalon2009e,
   title = {Natural extension as a limit of regular extensions},
   editor = {Augustin, T. and Coolen, F. and Troffaes, M.C.M. and Moral, S.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {327--336},
   year = {2009},
   doi = {},
   url = {http://www.sipta.org/isipta09/proceedings/papers/s012.pdf}
}
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Pelessoni, R., Vicig, P., Zaffalon, M. (2009). The pari-mutuel model. In Augustin, T., Coolen, F., Troffaes, M.C.M., Moral, S. (Eds), ISIPTA '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications, SIPTA, pp. 347–356.

The pari-mutuel model

@INPROCEEDINGS{zaffalon2009d,
   title = {The pari-mutuel model},
   editor = {Augustin, T. and Coolen, F. and Troffaes, M.C.M. and Moral, S.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '09: Proceedings of the Sixth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Pelessoni, R. and Vicig, P. and Zaffalon, M.},
   pages = {347--356},
   year = {2009},
   doi = {},
   url = {http://www.sipta.org/isipta09/proceedings/papers/s028.pdf}
}
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Piatti, A., Zaffalon, M., Trojani, F., Hutter, M. (2009). Limits of learning about a categorical latent variable under prior near-ignorance. International Journal of Approximate Reasoning 50, pp. 597–611.

Limits of learning about a categorical latent variable under prior near-ignorance

@ARTICLE{zaffalon2009a,
   title = {Limits of learning about a categorical latent variable under prior near-ignorance},
   journal = {International Journal of Approximate Reasoning},
   volume = {50},
   author = {Piatti, A. and Zaffalon, M. and Trojani, F. and Hutter, M.},
   pages = {597--611},
   year = {2009},
   doi = {10.1016/j.ijar.2008.08.003},
   url = {}
}
Download
Zaffalon, M., Miranda, E. (2009). Conservative inference rule for uncertain reasoning under incompleteness. Journal of Artificial Intelligence Research 34, pp. 757–821.

Conservative inference rule for uncertain reasoning under incompleteness

@ARTICLE{zaffalon2009c,
   title = {Conservative inference rule for uncertain reasoning under incompleteness},
   journal = {Journal of Artificial Intelligence Research},
   volume = {34},
   author = {Zaffalon, M. and Miranda, E.},
   pages = {757--821},
   year = {2009},
   doi = {10.1613/jair.2736},
   url = {}
}
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2008

Antonucci, A., Zaffalon, M. (2008). Decision-theoretic specification of credal networks: a unified language for uncertain modeling with sets of Bayesian networks. International Journal of Approximate Reasoning 49(2), pp. 345–361.

Decision-theoretic specification of credal networks: a unified language for uncertain modeling with sets of Bayesian networks

@ARTICLE{antonucci2008b,
   title = {Decision-theoretic specification of credal networks: a unified language for uncertain modeling with sets of {B}ayesian networks},
   journal = {International Journal of Approximate Reasoning},
   volume = {49},
   author = {Antonucci, A. and Zaffalon, M.},
   number = {2},
   pages = {345--361},
   year = {2008},
   doi = {10.1016/j.ijar.2008.02.005},
   url = {}
}
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Antonucci, A., Zaffalon, M., Yi, S., de Campos, C.P. (2008). Generalized loopy 2U: a new algorithm for approximate inference in credal networks. In Jaeger, M., Nielsen, T.D. (Eds), PGM'08: Proceedings of the Fourth European Workshop on Probabilistic Graphical Models, Hirtshals (Denmark), pp. 17–24.

Generalized loopy 2U: a new algorithm for approximate inference in credal networks

@INPROCEEDINGS{antonucci2008a,
   title = {Generalized loopy {2U}: a new algorithm for approximate inference in credal networks},
   editor = {Jaeger, M. and Nielsen, T.D.},
   address = {Hirtshals (Denmark)},
   booktitle = {{PGM'08}: Proceedings of the Fourth European Workshop on Probabilistic Graphical Models},
   author = {Antonucci, A. and Zaffalon, M. and Yi, S. and de Campos, C.P.},
   pages = {17--24},
   year = {2008},
   doi = {},
   url = {http://pgm08.cs.aau.dk/Papers/38_Paper.pdf}
}
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Corani, G., Zaffalon, M. (2008). Learning reliable classifiers from small or incomplete data sets: the naive credal classifier 2. Journal of Machine Learning Research 9, pp. 581–621.

Learning reliable classifiers from small or incomplete data sets: the naive credal classifier 2

@ARTICLE{corani2008d,
   title = {Learning reliable classifiers from small or incomplete data sets: the naive credal classifier 2},
   journal = {Journal of Machine Learning Research},
   volume = {9},
   author = {Corani, G. and Zaffalon, M.},
   pages = {581--621},
   year = {2008},
   doi = {},
   url = {http://jmlr.csail.mit.edu/papers/volume9/corani08b/corani08b.pdf}
}
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Corani, G., Zaffalon, M. (2008). JNCC2: an extension of naive Bayes classifier suited for small and incomplete data sets. Environmental Modelling & Software 23(7), pp. 960–961.

JNCC2: an extension of naive Bayes classifier suited for small and incomplete data sets

@ARTICLE{corani2008b,
   title = {{JNCC2}: an extension of naive {B}ayes classifier suited for small and incomplete data sets},
   journal = {Environmental Modelling & Software},
   volume = {23},
   author = {Corani, G. and Zaffalon, M.},
   number = {7},
   pages = {960--961},
   year = {2008},
   doi = {10.1016/j.envsoft.2008.01.004},
   url = {}
}
Download
Corani, G., Zaffalon, M. (2008). JNCC2: the Java implementation of naive credal classifier 2. Journal of Machine Learning Research 9, pp. 2695–2698.

JNCC2: the Java implementation of naive credal classifier 2

@ARTICLE{corani2008c,
   title = {{JNCC2}: the {J}ava implementation of naive credal classifier 2},
   journal = {Journal of Machine Learning Research},
   volume = {9},
   author = {Corani, G. and Zaffalon, M.},
   pages = {2695--2698},
   year = {2008},
   doi = {},
   url = {http://jmlr.csail.mit.edu/papers/volume9/corani08b/corani08b.pdf}
}
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Corani, G., Zaffalon, M. (2008). Naive credal classifier 2: an extension of naive Bayes for delivering robust classifications. In Proc. International Conference on Data Mining 2008 (DMIN '08).

Naive credal classifier 2: an extension of naive Bayes for delivering robust classifications

@INPROCEEDINGS{corani2008a,
   title = {Naive credal classifier 2: an extension of naive {B}ayes for delivering robust classifications},
   booktitle = {Proc. International Conference on Data Mining 2008 ({DMIN} '08)},
   author = {Corani, G. and Zaffalon, M.},
   year = {2008},
   doi = {},
   url = {}
}
Download
Corani, G., Zaffalon, M. (2008). Credal model averaging: an extension of Bayesian model averaging to imprecise probabilities. In Daelemans, W., Goethals, B., Morik, K. (Eds), Machine Learning and Knowledge Discovery in Databases, Lecture Notes in Computer Science 5211, Springer, Berlin / Heidelberg, pp. 257–271.

Credal model averaging: an extension of Bayesian model averaging to imprecise probabilities

@INCOLLECTION{corani2008e,
   title = {Credal model averaging: an extension of {B}ayesian model averaging to imprecise probabilities},
   editor = {Daelemans, W. and Goethals, B. and Morik, K.},
   publisher = {Springer, Berlin / Heidelberg},
   series = {Lecture Notes in Computer Science},
   volume = {5211},
   booktitle = {Machine Learning and Knowledge Discovery in Databases},
   author = {Corani, G. and Zaffalon, M.},
   pages = {257--271},
   year = {2008},
   doi = {10.1007/978-3-540-87479-9_35},
   url = {}
}
Download
Salvetti, A., Antonucci, A., Zaffalon, M. (2008). Spatially distributed identification of debris flow source areas by credal networks. In Sanchez-Marrè, M., Béjar, J., Comas, J., Rizzoli, A., Guariso, G. (Eds), iEMSs 2008: International Congress on Environmental Modelling and Software Integrating Sciences and Information Technology for Environmental Assessment and Decision Making (transactions of the 4th Biennial Meeting of the International Environmental Modelling and Software Society), iEMSs, Manno, Switzerland, pp. 380–387.

Spatially distributed identification of debris flow source areas by credal networks

@INPROCEEDINGS{antonucci2008c,
   title = {Spatially distributed identification of debris flow source areas by credal networks},
   editor = {Sanchez-Marr\`e, M. and B\'ejar, J. and Comas, J. and Rizzoli, A. and Guariso, G.},
   publisher = {iEMSs},
   address = {Manno, Switzerland},
   booktitle = {{iEMSs} 2008: International Congress on Environmental Modelling and Software Integrating Sciences and Information Technology for Environmental Assessment and Decision Making ({t}ransactions of the 4th Biennial Meeting of the International Environmental Modelling and Software Society)},
   author = {Salvetti, A. and Antonucci, A. and Zaffalon, M.},
   pages = {380--387},
   year = {2008},
   doi = {},
   url = {http://www.iemss.org/iemss2008/uploads/Main/S04-16-Salvetti_et_al-IEMSS2008.pdf}
}
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2007

Antonucci, A., Brühlmann, R., Piatti, A., Zaffalon, M. (2007). Credal networks for military identification problems. In de Cooman, G., Vejnarová, J., Zaffalon, M. (Eds), ISIPTA '07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications, Action M Agency, Prague (Czech Republic), pp. 1–10.

Credal networks for military identification problems

@INPROCEEDINGS{antonucci2007b,
   title = {Credal networks for military identification problems},
   editor = {de Cooman, G. and Vejnarov\'a, J. and Zaffalon, M.},
   publisher = {Action M Agency},
   address = {Prague (Czech Republic)},
   booktitle = {{ISIPTA} '07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Antonucci, A. and Br\"uhlmann, R. and Piatti, A. and Zaffalon, M.},
   pages = {1--10},
   year = {2007},
   doi = {},
   url = {http://www.sipta.org/isipta07/proceedings/papers/s066.pdf}
}
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Antonucci, A., Piatti, A., Zaffalon, M. (2007). Credal networks for operational risk measurement and management. In Apolloni, B., Howlett, R.J., Jain, L.C. (Eds), Proceedings of the 11th International Conference on Knowledge-based and Intelligent Information & Engineering Systems: KES2007, Lectures Notes in Computer Science 4693, Springer, pp. 604–611.

Credal networks for operational risk measurement and management

@INPROCEEDINGS{antonucci2007c,
   title = {Credal networks for operational risk measurement and management},
   editor = {Apolloni, B. and Howlett, R.J. and Jain, L.C.},
   publisher = {Springer},
   volume = {4693},
   booktitle = {Proceedings of the 11th International Conference on Knowledge-{b}ased and Intelligent Information & Engineering Systems: {KES2007}, Lectures Notes in Computer Science},
   author = {Antonucci, A. and Piatti, A. and Zaffalon, M.},
   pages = {604--611},
   year = {2007},
   doi = {10.1007/978-3-540-74827-4_76},
   url = {}
}
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Antonucci, A., Salvetti, A., Zaffalon, M. (2007). Credal networks for hazard assessment of debris flows. In Progress of Artificial Intelligence in Sustainability Science, Nova Science, Kropp, J., Scheffran, J., New York, pp. 125–132.

Credal networks for hazard assessment of debris flows

@INBOOK{antonucci2007d,
   title = {Credal networks for hazard assessment of debris flows},
   publisher = {Kropp, J., Scheffran, J.},
   address = {New York},
   series = {Nova Science},
   booktitle = {Progress of Artificial Intelligence in Sustainability Science},
   author = {Antonucci, A. and Salvetti, A. and Zaffalon, M.},
   pages = {125--132},
   year = {2007},
   doi = {},
   url = {}
}
Download
Antonucci, A., Zaffalon, M. (2007). Fast algorithms for robust classification with Bayesian nets. International Journal of Approximate Reasoning 44(3), pp. 200–223.

Fast algorithms for robust classification with Bayesian nets

@ARTICLE{antonucci2007a,
   title = {Fast algorithms for robust classification with {B}ayesian nets},
   journal = {International Journal of Approximate Reasoning},
   volume = {44},
   author = {Antonucci, A. and Zaffalon, M.},
   number = {3},
   pages = {200--223},
   year = {2007},
   doi = {10.1016/j.ijar.2006.07.011},
   url = {}
}
Download
Miranda, E., Zaffalon, M. (2007). Coherence graphs. In de Cooman, G., Vejnarova, J., Zaffalon, M. (Eds), ISIPTA '07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications, Action M Agency, Prague, pp. 297–306.

Coherence graphs

@INPROCEEDINGS{zaffalon2007c,
   title = {Coherence graphs},
   editor = {de Cooman, G. and Vejnarova, J. and Zaffalon, M.},
   publisher = {Action M Agency},
   address = {Prague},
   booktitle = {{ISIPTA} '07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Miranda, E. and Zaffalon, M.},
   pages = {297--306},
   year = {2007},
   doi = {},
   url = {http://www.sipta.org/isipta07/proceedings/papers/s060.pdf}
}
Download
Piatti, A., Trojani, F., Hutter, M., Zaffalon, M. (2007). Learning about a categorical latent variable under prior near-ignorance. In de Cooman, G., Vejnarova, J., Zaffalon, M. (Eds), ISIPTA '07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications, Action M Agency, Prague, pp. 357–364.

Learning about a categorical latent variable under prior near-ignorance

@INPROCEEDINGS{zaffalon2007b,
   title = {Learning about a categorical latent variable under prior near-ignorance},
   editor = {de Cooman, G. and Vejnarova, J. and Zaffalon, M.},
   publisher = {Action M Agency},
   address = {Prague},
   booktitle = {{ISIPTA} '07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications},
   author = {Piatti, A. and Trojani, F. and Hutter, M. and Zaffalon, M.},
   pages = {357--364},
   year = {2007},
   doi = {},
   url = {http://www.sipta.org/isipta07/proceedings/papers/s049.pdf}
}
Download
Vicig, P., Cozman, F., Zaffalon, M. (2007). Notes on “Notes on conditional previsions”. International Journal of Approximate Reasoning 44(3), pp. 358–365.

Notes on “Notes on conditional previsions”

@ARTICLE{zaffalon2007a,
   title = {Notes on “{N}otes on conditional previsions”},
   journal = {International Journal of Approximate Reasoning},
   volume = {44},
   author = {Vicig, P. and Cozman, F. and Zaffalon, M.},
   number = {3},
   pages = {358--365},
   year = {2007},
   doi = {10.1016/j.ijar.2006.07.018},
   url = {}
}
Download
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2006

Antonucci, A., Zaffalon, M., Ide, J.S., Cozman, F.G. (2006). Binarization algorithms for approximate updating in credal nets. In Penserini, L., Peppas, P., Perini, A. (Eds), STAIRS'06: Proceedings of the Third European Starting AI Researcher Symposium, IOS Press, Amsterdam (Netherlands), pp. 120–131.

Binarization algorithms for approximate updating in credal nets

@INPROCEEDINGS{antonucci2006b,
   title = {Binarization algorithms for approximate updating in credal nets},
   editor = {Penserini, L. and Peppas, P. and Perini, A.},
   publisher = {IOS Press},
   address = {Amsterdam (Netherlands)},
   booktitle = {{STAIRS'06}: Proceedings of the Third European Starting {AI} Researcher Symposium},
   author = {Antonucci, A. and Zaffalon, M. and Ide, J.S. and Cozman, F.G.},
   pages = {120--131},
   year = {2006},
   doi = {},
   url = {}
}
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Antonucci, A., Zaffalon, M. (2006). Equivalence between Bayesian and credal nets on an updating problem. In Lawry, J., Miranda, E., Bugarin, A., Li, S., Gil, M.A., Grzegorzewski, P., Hryniewicz, O. (Eds), Proceedings of Third International Conference on Soft Methods in Probability and Statistics (SMPS-2006), Springer, pp. 223–230.

Equivalence between Bayesian and credal nets on an updating problem

@INPROCEEDINGS{antonucci2006a,
   title = {Equivalence between {B}ayesian and credal nets on an updating problem},
   editor = {Lawry, J. and Miranda, E. and Bugarin, A. and Li, S. and Gil, M.A. and Grzegorzewski, P. and Hryniewicz, O.},
   publisher = {Springer},
   booktitle = {Proceedings of Third International Conference on Soft Methods in Probability and Statistics ({SMPS}-2006)},
   author = {Antonucci, A. and Zaffalon, M.},
   pages = {223--230},
   year = {2006},
   doi = {10.1007/3-540-34777-1_27},
   url = {}
}
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Antonucci, A., Zaffalon, M. (2006). Locally specified credal networks. In Studený, M., Vomlel, J. (Eds), PGM'06: Proceedings of the Third European Workshop on Probabilistic Graphical Models, Action M Agency, Prague (Czech Republic), pp. 25–34.

Locally specified credal networks

@INPROCEEDINGS{antonucci2006c,
   title = {Locally specified credal networks},
   editor = {Studen\'y, M. and Vomlel, J.},
   publisher = {Action M Agency},
   address = {Prague (Czech Republic)},
   booktitle = {{PGM'06}: Proceedings of the Third European Workshop on Probabilistic Graphical Models},
   author = {Antonucci, A. and Zaffalon, M.},
   pages = {25--34},
   year = {2006},
   doi = {},
   url = {http://www.utia.cas.cz/files/mtr/pgm06/26_paper.pdf}
}
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Corani, G., Edgar, C., Marshall, I., Wesnes, K., Zaffalon, M. (2006). Classification of dementia types from cognitive profiles data. In Fuernkranz, J., Scheffer, T., Spiliopoulou, M. (Eds), Knowledge Discovery in Databases: PKDD 2006, Lecture Notes in Computer Science 4213, Springer, Berlin / Heidelberg, pp. 470–477.

Classification of dementia types from cognitive profiles data

@INCOLLECTION{corani2006a,
   title = {Classification of dementia types from cognitive profiles data},
   editor = {Fuernkranz, J. and Scheffer, T. and Spiliopoulou, M.},
   publisher = {Springer, Berlin / Heidelberg},
   series = {Lecture Notes in Computer Science},
   volume = {4213},
   booktitle = {Knowledge Discovery in Databases: {PKDD} 2006},
   author = {Corani, G. and Edgar, C. and Marshall, I. and Wesnes, K. and Zaffalon, M.},
   pages = {470--477},
   year = {2006},
   doi = {10.1007/11871637_45},
   url = {}
}
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2005

Antonucci, A., Zaffalon, M. (2005). Fast algorithms for robust classification with Bayesian nets. In Cozman, F.G., Nau, R., Seidenfeld, T. (Eds), ISIPTA '05: Proceedings of the Fifth International Symposium on Imprecise Probabilities and Their Applications, SIPTA, pp. 11–20.

Fast algorithms for robust classification with Bayesian nets

@INPROCEEDINGS{antonucci2005a,
   title = {Fast algorithms for robust classification with {B}ayesian nets},
   editor = {Cozman, F.G. and Nau, R. and Seidenfeld, T.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '05: Proceedings of the Fifth International Symposium on Imprecise Probabilities and Their Applications},
   author = {Antonucci, A. and Zaffalon, M.},
   pages = {11--20},
   year = {2005},
   doi = {},
   url = {http://www.sipta.org/isipta05/proceedings/papers/s045.pdf}
}
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Corani, G. (2005). Air quality prediction in Milan: feed-forward neural networks, pruned neural networks and lazy learning. Ecological Modelling 185(2-4), pp. 513–529.

Air quality prediction in Milan: feed-forward neural networks, pruned neural networks and lazy learning

@ARTICLE{corani2005b,
   title = {Air quality prediction in {M}ilan: feed-forward neural networks, pruned neural networks and lazy learning},
   journal = {Ecological Modelling},
   volume = {185},
   author = {Corani, G.},
   number = {2-4},
   pages = {513--529},
   year = {2005},
   doi = {10.1016/j.ecolmodel.2005.01.008},
   url = {}
}
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Hutter, M., Zaffalon, M. (2005). Distribution of mutual information from complete and incomplete data. Computational Statistics and Data Analysis 48(3), pp. 633–657.

Distribution of mutual information from complete and incomplete data

@ARTICLE{zaffalon2005b,
   title = {Distribution of mutual information from complete and incomplete data},
   journal = {Computational Statistics and Data Analysis},
   volume = {48},
   author = {Hutter, M. and Zaffalon, M.},
   number = {3},
   pages = {633--657},
   year = {2005},
   doi = {10.1016/j.csda.2004.03.010},
   url = {}
}
Download
Piatti, A., Zaffalon, M., Trojani, F. (2005). Limits of learning from imperfect observations under prior ignorance: the case of the imprecise Dirichlet model. In Cozman, F.G., Nau, R., Seidenfeld, T. (Eds), ISIPTA '05: Proceedings of the Fourth International Symposium on Imprecise Probabilities and Their Applications, SIPTA, pp. 276–286.

Limits of learning from imperfect observations under prior ignorance: the case of the imprecise Dirichlet model

@INPROCEEDINGS{zaffalon2005d,
   title = {Limits of learning from imperfect observations under prior ignorance: the case of the imprecise {D}irichlet model},
   editor = {Cozman, F.G. and Nau, R. and Seidenfeld, T.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '05: Proceedings of the Fourth International Symposium on Imprecise Probabilities and Their Applications},
   author = {Piatti, A. and Zaffalon, M. and Trojani, F.},
   pages = {276--286},
   year = {2005},
   doi = {},
   url = {http://www.sipta.org/isipta05/proceedings/papers/s020.pdf}
}
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Zaffalon, M. (2005). Credible classification for environmental problems. Environmental modelling and software 20(8), pp. 1003–1012.

Credible classification for environmental problems

@ARTICLE{zaffalon2005a,
   title = {Credible classification for environmental problems},
   journal = {Environmental {m}odelling and {s}oftware},
   volume = {20},
   author = {Zaffalon, M.},
   number = {8},
   pages = {1003--1012},
   year = {2005},
   doi = {10.1016/j.envsoft.2004.10.006},
   url = {}
}
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Zaffalon, M. (2005). Conservative rules for predictive inference with incomplete data. In Cozman, F.G., Nau, R., Seidenfeld, T. (Eds), ISIPTA '05: Proceedings of the Fourth International Symposium on Imprecise Probabilities and Their Applications, SIPTA, pp. 406–415.

Conservative rules for predictive inference with incomplete data

@INPROCEEDINGS{zaffalon2005c,
   title = {Conservative rules for predictive inference with incomplete data},
   editor = {Cozman, F.G. and Nau, R. and Seidenfeld, T.},
   publisher = {SIPTA},
   booktitle = {{ISIPTA} '05: Proceedings of the Fourth International Symposium on Imprecise Probabilities and Their Applications},
   author = {Zaffalon, M.},
   pages = {406--415},
   year = {2005},
   doi = {},
   url = {http://www.sipta.org/isipta05/proceedings/papers/s038.pdf}
}
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Zaffalon, M., Hutter, M. (2005). Robust inference of trees. Annals of Mathematics and Artificial Intelligence 45(1–2), pp. 215–239.

Robust inference of trees

@ARTICLE{zaffalon2005e,
   title = {Robust inference of trees},
   journal = {Annals of Mathematics and Artificial Intelligence},
   volume = {45},
   author = {Zaffalon, M. and Hutter, M.},
   number = {1--2},
   pages = {215--239},
   year = {2005},
   doi = {10.1007/s10472-005-9007-9},
   url = {}
}
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2004

Antonucci, A., Salvetti, A., Zaffalon, M. (2004). Assessing debris flow hazard by credal nets. In Lopez-Diaz, M., Gil, M.A., Grzegorzewski, P., Hryniewicz, O., Lawry, J. (Eds), Proceedings of the Second International Conference on Soft Methods in Probability and Statistics (SMPS-2004) - Soft Methodology and Random Information Systems, Springer, pp. 125–132.

Assessing debris flow hazard by credal nets

@INPROCEEDINGS{antonucci2004b,
   title = {Assessing debris flow hazard by credal nets},
   editor = {Lopez-Diaz, M. and Gil, M.A. and Grzegorzewski, P. and Hryniewicz, O. and Lawry, J.},
   publisher = {Springer},
   booktitle = {Proceedings of the Second International Conference on Soft Methods in Probability and Statistics ({SMPS}-2004) - Soft Methodology and Random Information Systems},
   author = {Antonucci, A. and Salvetti, A. and Zaffalon, M.},
   pages = {125--132},
   year = {2004},
   doi = {},
   url = {}
}
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Antonucci, A., Salvetti, A., Zaffalon, M. (2004). Hazard assessment of debris flows by credal networks. In Pahl-Wostl, C., Schmidt, S., Rizzoli, A.E., Jakeman, A.J. (Eds), iEMSs 2004: Complexity and Integrated Resources Management, Transactions of the 2nd Biennial Meeting of the International Environmental Modelling and Software Society, iEMSs, pp. 98–103.

Hazard assessment of debris flows by credal networks

@INPROCEEDINGS{antonucci2004a,
   title = {Hazard assessment of debris flows by credal networks},
   editor = {Pahl-Wostl, C. and Schmidt, S. and Rizzoli, A.E. and Jakeman, A.J.},
   publisher = {iEMSs},
   booktitle = {{iEMSs} 2004: Complexity and Integrated Resources Management, Transactions of the 2nd Biennial Meeting of the International Environmental Modelling and Software Society},
   author = {Antonucci, A. and Salvetti, A. and Zaffalon, M.},
   pages = {98--103},
   year = {2004},
   doi = {},
   url = {http://www.iemss.org/iemss2004/pdf/ai/antohaza.pdf}
}
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de Cooman, G., Zaffalon, M. (2004). Updating beliefs with incomplete observations. Artificial Intelligence 159(1–2), pp. 75–125.

Updating beliefs with incomplete observations

@ARTICLE{zaffalon2004a,
   title = {Updating beliefs with incomplete observations},
   journal = {Artificial Intelligence},
   volume = {159},
   author = {de Cooman, G. and Zaffalon, M.},
   number = {1--2},
   pages = {75--125},
   year = {2004},
   doi = {10.1016/j.artint.2004.05.006},
   url = {}
}
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2003

de Cooman, G., Zaffalon, M. (2003). Updating with incomplete observations. In Kjærulff, U., Meek, C. (Eds), Proceedings of the 19th Conference on Uncertainty in Artificial Intelligence (UAI-2002), Morgan Kaufmann, pp. 142–150.

Updating with incomplete observations

@INPROCEEDINGS{zaffalon2003c,
   title = {Updating with incomplete observations},
   editor = {Kj\aerulff, U. and Meek, C.},
   publisher = {Morgan Kaufmann},
   booktitle = {Proceedings of the 19th Conference on Uncertainty in Artificial Intelligence ({UAI}-2002)},
   author = {de Cooman, G. and Zaffalon, M.},
   pages = {142--150},
   year = {2003},
   doi = {},
   url = {http://uai.sis.pitt.edu/papers/03/p142-de_cooman.pdf}
}
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Hutter, M., Zaffalon, M. (2003). Bayesian treatment of incomplete discrete data applied to mutual information and feature selection. In Günter, A., Kruse, R., Neumann, B. (Eds), Proceedings of the 26th German Conference on Artificial Intelligence (KI-2003), Lecture Notes in Computer Science 2821, Springer-Verlag, Heidelberg, pp. 396–406.

Bayesian treatment of incomplete discrete data applied to mutual information and feature selection

@INPROCEEDINGS{zaffalon2003d,
   title = {Bayesian treatment of incomplete discrete data applied to mutual information and feature selection},
   editor = {G\"unter, A. and Kruse, R. and Neumann, B.},
   publisher = {Springer-Verlag},
   address = {Heidelberg},
   series = {Lecture Notes in Computer Science},
   volume = {2821},
   booktitle = {Proceedings of the 26th German Conference on Artificial Intelligence ({KI}-2003)},
   author = {Hutter, M. and Zaffalon, M.},
   pages = {396--406},
   year = {2003},
   doi = {10.1007/978-3-540-39451-8_29},
   url = {}
}
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Zaffalon, M., Fagiuoli, E. (2003). Tree-based credal networks for classification. Reliable Computing 9(6), pp. 487–509.

Tree-based credal networks for classification

@ARTICLE{zaffalon2003b,
   title = {Tree-based credal networks for classification},
   journal = {Reliable Computing},
   volume = {9},
   author = {Zaffalon, M. and Fagiuoli, E.},
   number = {6},
   pages = {487--509},
   year = {2003},
   doi = {10.1023/A:1025822321743},
   url = {}
}
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Zaffalon, M., Wesnes, K., Petrini, O. (2003). Reliable diagnoses of dementia by the naive credal classifier inferred from incomplete cognitive data. Artificial Intelligence in Medicine 29(1–2), pp. 61–79.

Reliable diagnoses of dementia by the naive credal classifier inferred from incomplete cognitive data

@ARTICLE{zaffalon2003a,
   title = {Reliable diagnoses of dementia by the naive credal classifier inferred from incomplete cognitive data},
   journal = {Artificial Intelligence in Medicine},
   volume = {29},
   author = {Zaffalon, M. and Wesnes, K. and Petrini, O.},
   number = {1--2},
   pages = {61--79},
   year = {2003},
   doi = {10.1016/S0933-3657(03)00046-0},
   url = {}
}
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2002

Zaffalon, M. (2002). Exact credal treatment of missing data. Journal of Statistical Planning and Inference 105(1), pp. 105–122.

Exact credal treatment of missing data

@ARTICLE{zaffalon2002b,
   title = {Exact credal treatment of missing data},
   journal = {Journal of Statistical Planning and Inference},
   volume = {105},
   author = {Zaffalon, M.},
   number = {1},
   pages = {105--122},
   year = {2002},
   doi = {10.1016/S0378-3758(01)00206-3},
   url = {}
}
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Zaffalon, M. (2002). The naive credal classifier. Journal of Statistical Planning and Inference 105(1), pp. 5–21.

The naive credal classifier

@ARTICLE{zaffalon2002a,
   title = {The naive credal classifier},
   journal = {Journal of Statistical Planning and Inference},
   volume = {105},
   author = {Zaffalon, M.},
   number = {1},
   pages = {5--21},
   year = {2002},
   doi = {10.1016/S0378-3758(01)00201-4},
   url = {}
}
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Zaffalon, M., Hutter, M. (2002). Robust feature selection by mutual information distributions. In Darwiche, A., Friedman, N. (Eds), Proceedings of the 18th Conference on Uncertainty in Artificial Intelligence (UAI-2002), Morgan Kaufmann, pp. 577–584.

Robust feature selection by mutual information distributions

@INPROCEEDINGS{zaffalon2002c,
   title = {Robust feature selection by mutual information distributions},
   editor = {Darwiche, A. and Friedman, N.},
   publisher = {Morgan Kaufmann},
   booktitle = {Proceedings of the 18th Conference on Uncertainty in Artificial Intelligence ({UAI}-2002)},
   author = {Zaffalon, M. and Hutter, M.},
   pages = {577--584},
   year = {2002},
   doi = {},
   url = {http://uai.sis.pitt.edu/papers/02/p577-zaffalon.pdf}
}
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Zaffalon, M. (2002). Credal classification for mining environmental data. In Rizzoli, A.E., Jakeman, A.J. (Eds), iEMSs 2002: Integrated Assessment and Decision Support (transactions of the 1st Biennial Meeting of the International Environmental Modelling and Software Society), iEMSs, Manno, Switzerland, pp. 72–77.

Credal classification for mining environmental data

@INPROCEEDINGS{zaffalon2002d,
   title = {Credal classification for mining environmental data},
   editor = {Rizzoli, A.E. and Jakeman, A.J.},
   publisher = {iEMSs},
   address = {Manno, Switzerland},
   booktitle = {{iEMSs} 2002: Integrated Assessment and Decision Support ({t}ransactions of the 1st Biennial Meeting of the International Environmental Modelling and Software Society)},
   author = {Zaffalon, M.},
   pages = {72--77},
   year = {2002},
   doi = {},
   url = {http://www.iemss.org/iemss2002/proceedings/pdf/volume\%20due/95_zaffalon.pdf}
}
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2001

Zaffalon, M. (2001). Statistical inference of the naive credal classifier. In de Cooman, G., Fine, T.L., Seidenfeld, T. (Eds), ISIPTA '01: Proceedings of the Second International Symposium on Imprecise Probabilities and Their Applications, Shaker, The Netherlands, pp. 384–393.

Statistical inference of the naive credal classifier

@INPROCEEDINGS{zaffalon2001b,
   title = {Statistical inference of the naive credal classifier},
   editor = {de Cooman, G. and Fine, T.L. and Seidenfeld, T.},
   publisher = {Shaker},
   address = {The Netherlands},
   booktitle = {{ISIPTA} '01: Proceedings of the Second International Symposium on Imprecise Probabilities and Their Applications},
   author = {Zaffalon, M.},
   pages = {384--393},
   year = {2001},
   doi = {},
   url = {http://www.sipta.org/isipta01/proceedings/s035.pdf}
}
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Zaffalon, M. (2001). Robust discovery of tree-dependency structures. In de Cooman, G., Fine, T.L., Seidenfeld, T. (Eds), ISIPTA '01: Proceedings of the Second International Symposium on Imprecise Probabilities and Their Applications, Shaker, The Netherlands, pp. 394–403.

Robust discovery of tree-dependency structures

@INPROCEEDINGS{zaffalon2001c,
   title = {Robust discovery of tree-dependency structures},
   editor = {de Cooman, G. and Fine, T.L. and Seidenfeld, T.},
   publisher = {Shaker},
   address = {The Netherlands},
   booktitle = {{ISIPTA} '01: Proceedings of the Second International Symposium on Imprecise Probabilities and Their Applications},
   author = {Zaffalon, M.},
   pages = {394--403},
   year = {2001},
   doi = {},
   url = {http://www.sipta.org/isipta01/proceedings/s037.pdf}
}
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Zaffalon, M., Wesnes, K., Petrini, O. (2001). Credal classification for dementia screening. In Quaglini, S., Barahona, P., Andreassen, S. (Eds), AIME'01, Lecture Notes in Computer Science 2101, Springer-Verlag, pp. 67–76.

Credal classification for dementia screening

@INPROCEEDINGS{zaffalon2001d,
   title = {Credal classification for dementia screening},
   editor = {Quaglini, S. and Barahona, P. and Andreassen, S.},
   publisher = {Springer-Verlag},
   series = {Lecture Notes in Computer Science},
   volume = {2101},
   booktitle = {{AIME'01}},
   author = {Zaffalon, M. and Wesnes, K. and Petrini, O.},
   pages = {67--76},
   year = {2001},
   doi = {10.1007/3-540-48229-6_10},
   url = {}
}
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2000

Fagiuoli, E., Zaffalon, M. (2000). Tree-augmented naive credal classifiers. In Zadeh, L. A., Bouchon-Meunier, B. (Eds), IPMU 2000: Proceedings of the 8th Information Processing and Management of Uncertainty in Knowledge-based Systems Conference, Universidad Politècnica de Madrid, Madrid, pp. 1320–1327.

Tree-augmented naive credal classifiers

@INPROCEEDINGS{zaffalon2000a,
   title = {Tree-augmented naive credal classifiers},
   editor = {Zadeh, L. A. and Bouchon-Meunier, B.},
   publisher = {Universidad Polit\`ecnica de Madrid},
   address = {Madrid},
   booktitle = {{IPMU} 2000: Proceedings of the 8th Information Processing and Management of Uncertainty in Knowledge-{b}ased Systems Conference},
   author = {Fagiuoli, E. and Zaffalon, M.},
   pages = {1320--1327},
   year = {2000},
   doi = {},
   url = {}
}
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1999

Zaffalon, M. (1999). A credal approach to naive classification. In de Cooman, G., Cozman, F.G., Moral, S., Walley, P. (Eds), ISIPTA '99: Proceedings of the First International Symposium on Imprecise Probabilities and Their Applications, Universiteit Gent, Belgium, pp. 405–414.

A credal approach to naive classification

@INPROCEEDINGS{zaffalon1999a,
   title = {A credal approach to naive classification},
   editor = {de Cooman, G. and Cozman, F.G. and Moral, S. and Walley, P.},
   address = {Universiteit Gent, Belgium},
   booktitle = {{ISIPTA} '99: Proceedings of the First International Symposium on Imprecise Probabilities and Their Applications},
   author = {Zaffalon, M.},
   pages = {405--414},
   year = {1999},
   doi = {},
   url = {ftp://decsai.ugr.es/pub/utai/other/smc/isipta99/019.pdf}
}
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1998

Fagiuoli, E., Zaffalon, M. (1998). A note about redundancy in influence diagrams. International Journal of Approximate Reasoning 19(3–4), pp. 231–246.

A note about redundancy in influence diagrams

@ARTICLE{zaffalon1998b,
   title = {A note about redundancy in influence diagrams},
   journal = {International Journal of Approximate Reasoning},
   volume = {19},
   author = {Fagiuoli, E. and Zaffalon, M.},
   number = {3--4},
   pages = {231--246},
   year = {1998},
   doi = {10.1016/S0888-613X(98)10015-4},
   url = {}
}
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Fagiuoli, E., Zaffalon, M. (1998). 2U: an exact interval propagation algorithm for polytrees with binary variables. Artificial Intelligence 106(1), pp. 77–107.

2U: an exact interval propagation algorithm for polytrees with binary variables

@ARTICLE{zaffalon1998c,
   title = {{2U}: an exact interval propagation algorithm for polytrees with binary variables},
   journal = {Artificial Intelligence},
   volume = {106},
   author = {Fagiuoli, E. and Zaffalon, M.},
   number = {1},
   pages = {77--107},
   year = {1998},
   doi = {10.1016/S0004-3702(98)00089-7},
   url = {}
}
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Papers

Books

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2023

Casanova, A. (2023). Rationality and Desirability - a Foundational Study. Ph.D thesis, USI.

Rationality and Desirability - a Foundational Study

@PHDTHESIS{casanova2023,
   title = {Rationality and {D}esirability - a {F}oundational {S}tudy},
   author = {Casanova, A.},
   year = {2023},
   institution = {USI},
   doi = {},
   url = {}
}
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Scutari, M. (Ed), The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions, Chapman & Hall.

The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions

@BOOK{scutari2023a,
   title = {The {P}ragmatic {P}rogrammer for {M}achine {L}earning: {E}ngineering {A}nalytics and {D}ata {S}cience {S}olutions},
   editor = {Scutari, M.},
   publisher = {Chapman & Hall},
   year = {2023},
   doi = {10.1201/9780429292835},
   url = {}
}
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2022

Schürch M. P. (2022). Contributions to scalable Gaussian processes. Ph.D thesis, USI.

Contributions to scalable Gaussian processes

@PHDTHESIS{schurch2022,
   title = {Contributions to scalable {G}aussian processes},
   author = {Sch\"urch M. P.},
   year = {2022},
   institution = {USI},
   doi = {},
   url = {}
}
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2018

Scanagatta, M. (2018). Advancements in Bayesian network structure learning. Ph.D thesis, Università della Svizzera italiana.

Advancements in Bayesian network structure learning

@PHDTHESIS{scanagatta2018c,
   title = {Advancements in {B}ayesian network structure learning},
   author = {Scanagatta, M.},
   year = {2018},
   institution = {Universit\`a della Svizzera italiana},
   doi = {},
   url = {}
}
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2013

Mauá, D.D. (2013). Algorithms and Complexity Results for Discrete Probabilistic Reasoning Tasks. Ph.D thesis, Università della Svizzera italiana.

Algorithms and Complexity Results for Discrete Probabilistic Reasoning Tasks

@PHDTHESIS{maua2013,
   title = {Algorithms and {C}omplexity {R}esults for {D}iscrete {P}robabilistic {R}easoning {T}asks},
   author = {Mau\'a, D.D.},
   year = {2013},
   institution = {Universit\`a della Svizzera italiana},
   doi = {},
   url = {http://doc.rero.ch/record/203103?ln=en}
}
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2008

Antonucci, A. (2008). Imprecise probabilistic graphical models: equivalent representations, inference algorithms and applications. Ph.D thesis, Università della Svizzera Italiana.

Imprecise probabilistic graphical models: equivalent representations, inference algorithms and applications

@PHDTHESIS{antonucci,
   title = {Imprecise probabilistic graphical models: equivalent representations, inference algorithms and applications},
   author = {Antonucci, A.},
   year = {2008},
   institution = {Universit\`a della Svizzera Italiana},
   doi = {},
   url = {http://doc.rero.ch/record/10745?ln=en}
}
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2007

de Cooman, G., Vejnarova, J., Zaffalon, M. (Eds), ISIPTA '07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications, Action M Agency, Prague.

ISIPTA '07: Proceedings of the Fifth International Symposium on Imprecise Probability: Theories and Applications

@BOOK{zaffalon2007d,
   title = {{ISIPTA} '07: {P}roceedings of the {F}ifth {I}nternational {S}ymposium on {I}mprecise {P}robability: {T}heories and {A}pplications},
   editor = {de Cooman, G. and Vejnarova, J. and Zaffalon, M.},
   publisher = {Action M Agency},
   address = {Prague},
   year = {2007},
   doi = {},
   url = {http://www.sipta.org/isipta07/proceedings/}
}
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2003

Bernard, J.-M., Seidenfeld, T., Zaffalon, M. (Eds), ISIPTA '03: Proceedings of the Third International Symposium on Imprecise Probabilities and Their Applications, Proceedings in Informatics 18, Carleton Scientific, Canada.

ISIPTA '03: Proceedings of the Third International Symposium on Imprecise Probabilities and Their Applications

@BOOK{zaffalon2003e,
   title = {{ISIPTA} '03: {P}roceedings of the {T}hird {I}nternational {S}ymposium on {I}mprecise {P}robabilities and {T}heir {A}pplications},
   editor = {Bernard, J.-M. and Seidenfeld, T. and Zaffalon, M.},
   publisher = {Carleton Scientific},
   address = {Canada},
   year = {2003},
   doi = {},
   url = {http://www.sipta.org/isipta03/proc/}
}
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