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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2021

Mellace, S., Kanjirangat, V., Antonucci, A. (2021). Relation clustering in narrative knowledge graphs. In Accepted for AI4Narratives Workshop at 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence.

Relation clustering in narrative knowledge graphs

@INPROCEEDINGS{vani2021a,
   title = {Relation clustering in narrative knowledge graphs},
   booktitle = {Accepted for {AI4Narratives} Workshop at 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence},
   author = {Mellace, S., Kanjirangat, V. and Antonucci, A.},
   year = {2021},
   url = {https://arxiv.org/abs/2011.13647}
}
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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}
}
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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},
   url = {https://www.aaai.org/Library/FLAIRS/flairs20contents.php}
}
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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), JMLR.org.

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 = {JMLR.org},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {Azzimonti, L. and Corani, G. and Scutari, M.},
   year = {2020},
   url = {https://pgm2020.cs.aau.dk/}
}
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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}
}
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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}
}
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Benavoli, A., Azzimonti, D., Piga, D. (2020). Skew gaussian processes for classification. Machine Learning 109.

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.},
   year = {2020},
   doi = {10.1007/s10994-020-05906-3}
}
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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}
}
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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, PMLR, Aalborg, Denmark.

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},
   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.},
   year = {2020}
}
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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.

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},
   author = {Cannelli, L. and Facchinei, F. and Scutari, G. and Kungurtsev, V.},
   year = {2020},
   doi = {10.1109/TAC.2020.3033490}
}
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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},
   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}
}
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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 Proceedings ECML - PKDD 2020.

Probabilistic reconciliation of hierarchical forecast via Bayes’ rule

@INPROCEEDINGS{corani2020a,
   title = {Probabilistic reconciliation of hierarchical forecast via {B}ayes’ rule},
   booktitle = {Proceedings {ECML} - {PKDD} 2020},
   author = {Corani, G. and Azzimonti, D. and Augusto, J.P.S.C. and Zaffalon, M.},
   year = {2020}
}
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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 = {https://doi.org/10.1016/j.neucom.2020.07.117},
   url = {http://www.sciencedirect.com/science/article/pii/S092523122031328X}
}
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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), JMLR.org.

Poset representations for sets of elementary triplets

@INPROCEEDINGS{Linda2020c,
   title = {Poset representations for sets of elementary triplets},
   publisher = {JMLR.org},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {van der Gaag, L.C. and Bolt, J.H.},
   year = {2020},
   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), JMLR.org.

Building causal interaction models by recursive unfolding

@INPROCEEDINGS{Linda2020a,
   title = {Building causal interaction models by recursive unfolding},
   publisher = {JMLR.org},
   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.},
   year = {2020},
   url = {https://pgm2020.cs.aau.dk/index.php/accepted-papers/}
}
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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}
}
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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, PMLR, Aalborg, Denmark.

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},
   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.},
   year = {2020},
   url = {https://pgm2020.cs.aau.dk}
}
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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 2020), 42nd European Conference on Information Retrieval, 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} 2020), 42nd European Conference on Information Retrieval},
   author = {Kanjirangat, V. and Mellace, S. and Antonucci, A.},
   year = {2020},
   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.

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.},
   year = {2020},
   url = {http://alt.qcri.org/semeval2020/}
}
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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}
}
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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.

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.},
   year = {2020},
   doi = {10.1016/j.automatica.2020.108914},
   url = {http://www.sciencedirect.com/science/article/pii/S0005109820301126}
}
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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}
}
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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},
   url = {https://sites.google.com/view/wicrs2020}
}
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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}
}
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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, PMLR, Aalborg, Denmark.

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},
   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.},
   year = {2020},
   url = {https://pgm2020.cs.aau.dk}
}
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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), Berlin, Germany.

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},
   address = {Berlin, Germany},
   booktitle = {21st {IFAC} World Congress ({IFAC} 2020)},
   author = {Mejari, M. and Breschi, V. and Naik, V.V. and Piga, D.},
   year = {2020},
   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}
}
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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}
}
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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}
}
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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.

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 kalman filter},
   journal = {{MDPI} Machines},
   author = {Roveda, L. and Bussolan, A. and Braghin, F. and Piga, D.},
   year = {2020},
   doi = {https://doi.org/10.3390/machines8040067}
}
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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.

A control framework Definition to overcome Position/Interaction dynamics uncertainties in force-controlled tasks

@INPROCEEDINGS{Roveda2020f,
   title = {A control framework {D}efinition 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.},
   year = {2020},
   doi = {10.1109/ICRA40945.2020.9197141}
}
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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}
}
Download
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.

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.},
   year = {2020},
   doi = {10.1109/UR49135.2020.9144761}
}
Download
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.

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},
   author = {Roveda, L. and Maskani, J. and Franceschi, P. and Arash, A. and Braghin, F. and Molinari Tosatti, L. and Pedrocchi, N.},
   year = {2020},
   doi = {10.1007/s10846- 020-01183-3}
}
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.

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

@ARTICLE{Roveda2020d,
   title = {Robust state dependent riccati equation variable impedance control for robotic force-tracking tasks},
   journal = {International Journal of Intelligent Robotics and Applications},
   publisher = {Springer},
   author = {Roveda, L. and Piga, D.},
   year = {2020},
   doi = {10.1007/s41315-020-00153-0}
}
Download
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.

Interaction force computation exploiting environment Stiffness estimation for sensorless robot applications

@INPROCEEDINGS{Roveda2020g,
   title = {Interaction force computation exploiting environment {S}tiffness estimation for sensorless robot applications},
   booktitle = {{IEEE} Metrology for Industry 4.0 and {IoT} 2020},
   author = {Roveda, L. and Piga, D.},
   year = {2020},
   doi = {10.1109/MetroInd4.0IoT48571.2020.9138189}
}
Download
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.

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},
   author = {Roveda, L. and Savani, L. and Arlati, S. and Dinon, T. and Legnani, G. and Molinari Tosatti, L.},
   year = {2020},
   doi = {https://doi.org/10.1016/j.ergon.2020.102991}
}
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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}
}
Download
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).

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.},
   year = {2020},
   doi = {10.1109/MetroInd4.0IoT48571.2020.9138183}
}
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), ACM.

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.},
   year = {2020},
   url = {http://www.icmlc.org/}
}
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).

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.},
   year = {2020},
   url = {https://dl.acm.org/doi/pdf/10.1145/3336191.3371815}
}
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Zaffalon, M., Antonucci, A., Cabañas, R. (2020). Structural causal models are (solvable by) credal networks. In Proceedings of the 10th International Conference on Probabilistic Graphical Models (PGM 2020), JMLR.org.

Structural causal models are (solvable by) credal networks

@INPROCEEDINGS{zaffalon2020b,
   title = {Structural causal models are (solvable by) credal networks},
   publisher = {JMLR.org},
   booktitle = {Proceedings of the 10th International Conference on Probabilistic Graphical Models ({PGM} 2020)},
   author = {Zaffalon, M. and Antonucci, A. and Cabañas, R.},
   year = {2020},
   url = {https://pgm2020.cs.aau.dk/}
}
Download
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},
   url = {https://aaai.org/ocs/index.php/FLAIRS/FLAIRS19/paper/view/18228/17346}
}
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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).

Credal sentential decision diagrams

@INPROCEEDINGS{supsi2019b,
   title = {Credal sentential decision diagrams},
   booktitle = {Proceedings of the Eleventh International Symposium on Imprecise Probability: Theories and Applications ({ISIPTA} '19)},
   author = {Antonucci, A. and Facchini, A. and Mattei, L.},
   year = {2019},
   url = {http://www.isipta2019.ugent.be/contributions/antonucci19.pdf}
}
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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}
}
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}
}
Download
Azzimonti, D., Ginsbourger, D., Chevalier, C., Bect, J., Richet, Y. (2019). Adaptive design of experiments for conservative estimation of excursion sets. Technometrics, pp. 1–30.

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},
   author = {Azzimonti, D. and Ginsbourger, D. and Chevalier, C. and Bect, J. and Richet, Y.},
   pages = {1--30},
   year = {2019},
   doi = {10.1080/00401706.2019.1693427}
}
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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}
}
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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}
}
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},
   url = {http://proceedings.mlr.press/v103/benavoli19a/benavoli19a.pdf}
}
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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},
   url = {http://www.sipta.org/isipta19/contributions/bolt19.pdf}
}
Download
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}
}
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}
}
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},
   url = {https://www.sciencedirect.com/science/article/pii/S001379441830451X?via%3Dihub}
}
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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 = {https://doi.org/10.3390/su11092674}
}
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}
}
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},
   url = {http://www.sipta.org/isipta19/contributions/correia19.pdf}
}
Download
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}
}
Download
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}
}
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},
   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 BioASQ: Large-Scale Biomedical Semantic Indexing and Question Answering: Workshop of ECML/PKDD 2019, Springer, Lecture Notes in Computer Science.

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 = {{BioASQ}: Large-Scale Biomedical Semantic Indexing and Question Answering: Workshop of {ECML/PKDD} 2019},
   author = {Kanjirangat, V. and Oita, M. and Oezdemir-Zaech, F.},
   year = {2019},
   url = {http://bioasq.org/}
}
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}
}
Download
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},
   url = {http://www.sipta.org/isipta19/contributions/renooij19.pdf}
}
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},
   url = {https://drive.google.com/file/d/1PkckPpeLUOP_Oeik_q4MprD6ZJeekqHZ/view}
}
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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 = {https://doi.org/10.3390/robotics8030065}
}
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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}
}
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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}
}
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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).

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},
   year = {2019},
   doi = {10.1109/JLT.2019.2922586}
}
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}
}
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Oita, M. (2019). Incremental alignment of metaphoric language model for poetry composition. In Computing Conference, 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 = {Computing Conference},
   author = {Oita, M.},
   pages = {834--845},
   year = {2019},
   doi = {10.1007/978-3-030-22871-2_59}
}
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Piga, D. (2019). Finite-horizon integration for continuous-time identification: bias analysis and application to variable stiffness actuators. International Journal of Control, pp. 1–14.

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},
   author = {Piga, D.},
   pages = {1--14},
   year = {2019},
   doi = {10.1080/00207179.2018.1557348}
}
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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}
}
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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}
}
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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}
}
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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}
}
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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}
}
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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}
}
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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}
}
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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}
}
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Zaffalon, M., Miranda, E. (2019). Desirability foundations of robust rational decision making. Synthese.

Desirability foundations of robust rational decision making

@ARTICLE{zaffalon2019a,
   title = {Desirability foundations of robust rational decision making},
   journal = {Synthese},
   publisher = {Springer},
   author = {Zaffalon, M. and Miranda, E.},
   year = {2019},
   doi = {10.1007/s11229-018-02010-x}
}
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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}
}
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Antonucci, A., Facchini, A. (2018). Set-valued probabilistic sentential decision diagrams. In Proceedings of the 5th Workshop on Probabilistic Logic Programming.

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.},
   year = {2018},
   url = {http://stoics.org.uk/plp/plp2018/}
}
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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}
}
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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}
}
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}
}
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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}
}
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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}
}
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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}
}
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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},
   url = { https://aaai.org/ocs/index.php/FLAIRS/FLAIRS18/paper/download/17696/16792}
}
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},
   url = {http://auai.org/uai2018/proceedings/papers/42.pdf}
}
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}
}
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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}
}
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}
}
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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}
}
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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}
}
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}
}
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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}
}
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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}
}
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}
}
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}
}
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},
   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, 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},
   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},
   url = {http://proceedings.mlr.press/v62/benavoli17b/benavoli17b.pdf}
}
Download
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},
   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},
   url = {http://qpl.science.ru.nl/papers/QPL_2017_paper_4.pdf}
}
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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}
}
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}
}
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), 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}
}
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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}
}
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}
}
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}
}
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},
   url = {http://proceedings.mlr.press/v73/scanagatta17a.html}
}
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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}
}
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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}
}
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}
}
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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}
}
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top

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}
}
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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}
}
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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},
   url = {http://jmlr.org/papers/volume17/benavoli16a/benavoli16a.pdf}
}
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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}
}
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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.

Quantum rational preferences and desirability

@INPROCEEDINGS{benavoli2016h,
   title = {Quantum rational preferences and desirability},
   journal = {{ArXiv} {e}-{p}rints 1610.06764},
   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.},
   year = {2016},
   url = {http://arxiv.org/abs/1610.06764}
}
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}
}
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}
}
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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}
}
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}
}
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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}
}
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}
}
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}
}
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}
}
Download
Mangili, F. (2016). A prior near-ignorance Gaussian process model for nonparametric regression. International Journal of Approximate Reasoning.

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 },
   author = {Mangili, F.},
   year = {2016},
   doi = {http://dx.doi.org/10.1016/j.ijar.2016.07.005}
}
Download
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},
   url = {http://link.springer.com/content/pdf/bbm%3A978-3-319-39583-8%2F1.pdf}
}
Download
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}
}
Download
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}
}
Download
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}
}
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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.

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},
   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},
   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},
   url = {http://www.sipta.org/isipta15/data/paper/32.pdf}
}
Download
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}
}
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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},
   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}
}
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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}
}
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), 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},
   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}
}
Download
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), 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},
   booktitle = {Proceedings of the 18th International Conference on Artificial Intelligence ({AISTAT} 2015)},
   author = {Benavoli, A. and Mangili, F.},
   pages = {74--82},
   year = {2015},
   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}
}
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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}
}
Download
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},
   url = {http://www.comp.hkbu.edu.hk/~cib/2015/Dec/iib_vol16no1.pdf}
}
Download
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}
}
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}
}
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}
}
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}
}
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}
}
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},
   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}
}
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}
}
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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}
}
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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}
}
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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},
   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.

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},
   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},
   url = {http://papers.nips.cc/paper/5803-learning-bayesian-networks-with-thousands-of-variables}
}
Download
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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}
}
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}
}
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}
}
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}
}
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}
}
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), 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},
   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.},
   pages = {1026--1034},
   year = {2014},
   url = {http://proceedings.mlr.press/v32/benavoli14.html}
}
Download
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}
}
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},
   url = {http://papers.nips.cc/paper/5472-global-sensitivity-analysis-for-map-inference-in-graphical-models.pdf}
}
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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}
}
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},
   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}
}
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}
}
Download
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}
}
Download
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.

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.},
   year = {2014}
}
Download
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}
}
Download
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}
}
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}
}
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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}
}
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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}
}
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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}
}
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}
}
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},
   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}
}
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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}
}
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},
   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},
   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}
}
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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}
}
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}
}
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}
}
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}
}
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}
}
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}
}
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}
}
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}
}
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}
}
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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}
}
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},
   url = {http://www.sipta.org/isipta13/proceedings/papers/s025.pdf}
}
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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}
}
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}
}
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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}
}
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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}
}
Download
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}
}
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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}
}
Download
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}
}
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}
}
Download
Benavoli, A., Noack, B. (2012). Pushing Kalman's idea to the extremes. In In Information Fusion (FUSION), 2012 Proc. of the 15th International Conference on, pp. 1–8.

Pushing Kalman's idea to the extremes

@INPROCEEDINGS{benavoli2012e,
   title = {Pushing {K}alman's idea to the extremes},
   booktitle = {In Information Fusion ({FUSION}), 2012 Proc. {o}f the 15th International Conference on},
   author = {Benavoli, A. and Noack, B.},
   pages = {1--8},
   year = {2012}
}
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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}
}
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}
}
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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}
}
Download
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}
}
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}
}
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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},
   url = {http://www.jair.org/media/3625/live-3625-6282-jair.pdf}
}
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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}
}
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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},
   url = {http://icml.cc/2012/papers/728.pdf}
}
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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},
   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},
   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}
}
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}
}
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top

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}
}
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}
}
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},
   url = {http://www.sipta.org/isipta11/proceedings/papers/s032.pdf}
}
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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},
   url = {http://www.lidi.info.unlp.edu.ar/WorldComp2011-Mirror/IPC5150.pdf}
}
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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}
}
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}
}
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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},
   url = {http://www.sipta.org/isipta11/proceedings/papers/s027.pdf}
}
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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}
}
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},
   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},
   url = {http://ijcai.org/papers11/Papers/IJCAI11-352.pdf}
}
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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},
   url = {http://jmlr.csail.mit.edu/papers/volume12/decampos11a/decampos11a.pdf}
}
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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}
}
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}
}
Download
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}
}
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},
   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},
   url = {http://leo.ugr.es/sipta/isipta11/proceedings/papers/s035.pdf}
}
Download
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},
   url = {http://www.sipta.org/isipta11/proceedings/papers/s030.pdf}
}
Download
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},
   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}
}
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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}
}
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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}
}
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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},
   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}
}
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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}
}
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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}
}
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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}
}
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}
}
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}
}
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}
}
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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}
}
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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}
}
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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}
}
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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}
}
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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},
   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}
}
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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}
}
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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},
   url = {http://www.sipta.org/isipta09/proceedings/papers/s043.pdf}
}
Download
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}
}
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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}
}
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},
   url = {http://isif.org/fusion/proceedings/fusion09CD/data/papers/0345.pdf}
}
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de Campos, C.P., Cozman, F.G., Luna, J.E.O. (2009). Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence. Journal of Applied Logic 7(2), pp. 137–154.

Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence

@ARTICLE{decampos2009d,
   title = {Assembling a consistent set of sentences in relational probabilistic logic with stochastic independence},
   journal = {Journal of Applied Logic},
   volume = {7},
   author = {de Campos, C.P. and Cozman, F.G. and Luna, J.E.O.},
   number = {2},
   pages = {137--154},
   year = {2009},
   doi = {10.1016/j.jal.2007.11.002}
}
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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}
}
Download
de Campos, C.P., Zhang, L., Tong, Y., Ji, Q. (2009). Semi-qualitative probabilistic networks in computer vision problems. Journal of Statistical Theory and Practice 3(1), pp. 197–210.

Semi-qualitative probabilistic networks in computer vision problems

@ARTICLE{decampos2009c,
   title = {Semi-qualitative probabilistic networks in computer vision problems},
   journal = {Journal of Statistical Theory and Practice},
   publisher = {Grace Scientific Publishing LLC},
   volume = {3},
   author = {de Campos, C.P. and Zhang, L. and Tong, Y. and Ji, Q.},
   number = {1},
   pages = {197--210},
   year = {2009},
   doi = {10.1080/15598608.2009.10411920}
}
Download
de Campos, C.P., Zhang, L., Tong, Y., Ji, Q. (2009). Semi-qualitative probabilistic networks in computer vision problems. In Coolen-Schrijner, P., Coolen, F., Troffaes, M.C.M., Augustin, T. (Eds), Imprecision in Statistical Theory and Practice., Grace Scientific Publishing LLC, Greensboro, North-Carolina, USA, pp. 207–220.

Semi-qualitative probabilistic networks in computer vision problems

@INBOOK{decampos2009a,
   title = {Semi-qualitative probabilistic networks in computer vision problems},
   editor = {Coolen-Schrijner, P. and Coolen, F. and Troffaes, M.C.M. and Augustin, T.},
   publisher = {Grace Scientific Publishing LLC},
   address = {Greensboro, North-Carolina, USA},
   booktitle = {Imprecision in Statistical Theory and Practice.},
   author = {de Campos, C.P. and Zhang, L. and Tong, Y. and Ji, Q.},
   pages = {207--220},
   year = {2009},
   url = {http://www.amazon.com/Imprecision-Statistical-Practice-Pauline-Coolen-Schrijner/dp/0982399804}
}
Download
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},
   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},
   url = {http://www.sipta.org/isipta09/proceedings/papers/s060.pdf}
}
Download
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}
}
Download
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}
}
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}
}
Download
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},
   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},
   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}
}
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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}
}
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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}
}
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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},
   url = {http://pgm08.cs.aau.dk/Papers/38_Paper.pdf}
}
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de Campos, C.P., Ji, Q. (2008). Improving Bayesian network parameter learning using constraints. In 19th International Conference on Pattern Recognition (ICPR), pp. 1–4.

Improving Bayesian network parameter learning using constraints

@INPROCEEDINGS{decampos2008d,
   title = {Improving {B}ayesian network parameter learning using constraints},
   booktitle = {19th International Conference on Pattern Recognition ({ICPR})},
   author = {de Campos, C.P. and Ji, Q.},
   pages = {1--4},
   year = {2008},
   doi = {10.1109/ICPR.2008.4761287}
}
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de Campos, C., Ji, Q. (2008). Strategy selection in influence diagrams using imprecise probabilities. In Proceedings of the Twenty-fourth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-08), AUAI Press, Corvallis, Oregon, pp. 121–128.

Strategy selection in influence diagrams using imprecise probabilities

@INPROCEEDINGS{decampos2008b,
   title = {Strategy selection in influence diagrams using imprecise probabilities},
   publisher = {AUAI Press},
   address = {Corvallis, Oregon},
   booktitle = {Proceedings of the Twenty-{f}ourth Conference Annual Conference on Uncertainty in Artificial Intelligence ({UAI}-08)},
   author = {de Campos, C. and Ji, Q.},
   pages = {121--128},
   year = {2008},
   url = {http://uai.sis.pitt.edu/papers/08/p121-de_campos.pdf