Structured Machine Learning Group

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2018

Learning SMT(LRA) Constraints using SMT Solvers Samuel Kolb, Stefano Teso, Andrea Passerini, and Luc De Raedt. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, {IJCAI-18}.
@inproceedings {ijcai2018-323,
    author = { Kolb, Samuel and Teso, Stefano and Passerini, Andrea and Raedt, Luc De },
    title = "Learning SMT(LRA) Constraints using SMT Solvers",
    booktitle = "Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, {IJCAI-18}",
    publisher = "International Joint Conferences on Artificial Intelligence Organization",
    pages = "2333--2340",
    year = "2018",
    month = "7",
    doi = "10.24963/ijcai.2018/323",
    url = "https://doi.org/10.24963/ijcai.2018/323",
}
Pyconstruct: Constraint Programming Meets Structured Prediction Paolo Dragone, Stefano Teso, and Andrea Passerini. In Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, {IJCAI-18}.
@inproceedings {ijcai2018-850,
    author = { Dragone, Paolo and Teso, Stefano and Passerini, Andrea },
    title = "Pyconstruct: Constraint Programming Meets Structured Prediction",
    booktitle = "Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, {IJCAI-18}",
    publisher = "International Joint Conferences on Artificial Intelligence Organization",
    pages = "5823--5825",
    year = "2018",
    month = "7",
    doi = "10.24963/ijcai.2018/850",
    url = "https://doi.org/10.24963/ijcai.2018/850",
}
Constructive Preference Elicitation Paolo Dragone, Stefano Teso, and Andrea Passerini. In Frontiers in Robotics and AI.
@article {frontiers2018,
    author = { Dragone, Paolo and Teso, Stefano and Passerini, Andrea },
    title = "Constructive Preference Elicitation",
    journal = "Frontiers in Robotics and AI",
    volume = "4",
    pages = "71",
    year = "2018",
    url = "https://www.frontiersin.org/article/10.3389/frobt.2017.00071",
    doi = "10.3389/frobt.2017.00071",
    issn = "2296-9144",
}
Learning Constraints from Examples Luc De Raedt, Andrea Passerini, and Stefano Teso. In Proceedings of the 32nd Conference on Artificial Intelligence (AAAI).
@inproceedings {aaai18_cl,
    author = { Raedt, Luc De and Passerini, Andrea and Teso, Stefano },
    title = "Learning Constraints from Examples",
    booktitle = "Proceedings of the 32nd Conference on Artificial Intelligence (AAAI)",
    url = "papers/aaai18_cl.pdf",
    year = "2018",
}
Decomposition Strategies for Constructive Preference Elicitation Paolo Dragone, Stefano Teso, and Andrea Passerini. In Proceedings of the 32nd Conference on Artificial Intelligence (AAAI).
@inproceedings {aaai18_sketch,
    author = { Dragone, Paolo and Teso, Stefano and Passerini, Andrea },
    title = "Decomposition Strategies for Constructive Preference Elicitation",
    booktitle = "Proceedings of the 32nd Conference on Artificial Intelligence (AAAI)",
    url = "papers/aaai18_sketch.pdf",
    year = "2018",
}
Constructive Preference Elicitation over Hybrid Combinatorial Spaces Paolo Dragone, Stefano Teso, and Andrea Passerini. In Proceedings of the 32nd Conference on Artificial Intelligence (AAAI).
@inproceedings {aaai18_store,
    author = { Dragone, Paolo and Teso, Stefano and Passerini, Andrea },
    title = "Constructive Preference Elicitation over Hybrid Combinatorial Spaces",
    booktitle = "Proceedings of the 32nd Conference on Artificial Intelligence (AAAI)",
    url = "papers/aaai18_store.pdf",
    year = "2018",
}
2017

Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects Seyed Mostafa Kia, Sandro Vega Pons, Nathan Weisz, and Andrea Passerini. In Frontiers in Neuroscience.
@article {fnins17,
    author = { Kia, Seyed Mostafa and Vega Pons, Sandro and Weisz, Nathan and Passerini, Andrea },
    title = "Interpretability of Multivariate Brain Maps in Linear Brain Decoding: Definition, and Heuristic Quantification in Multivariate Analysis of MEG Time-Locked Effects",
    journal = "Frontiers in Neuroscience",
    volume = "10",
    pages = "619",
    year = "2017",
    url = "http://journal.frontiersin.org/article/10.3389/fnins.2016.00619",
    doi = "10.3389/fnins.2016.00619",
}
Coactive Critiquing: Elicitation of Preferences and Features Stefano Teso, Paolo Dragone, and Andrea Passerini. In Proceedings of the 31st Conference on Artificial Intelligence (AAAI).
@inproceedings {aaai17,
    author = { Teso, Stefano and Dragone, Paolo and Passerini, Andrea },
    title = "Coactive Critiquing: Elicitation of Preferences and Features",
    booktitle = "Proceedings of the 31st Conference on Artificial Intelligence (AAAI)",
    url = "papers/aaai2017.pdf",
    year = "2017",
}
Efficient Weighted Model Integration via SMT-Based Predicate Abstraction Paolo Morettin, Andrea Passerini, and Roberto Sebastiani. In Proc. Int. Joint Conference on Artificial Intelligence (IJCAI).
@inproceedings {ijcai17,
    author = { Morettin, Paolo and Passerini, Andrea and Sebastiani, Roberto },
    title = "Efficient Weighted Model Integration via SMT-Based Predicate Abstraction",
    booktitle = "Proc. Int. Joint Conference on Artificial Intelligence (IJCAI)",
    year = "2017",
    url = "papers/ijcai17.pdf",
}
Constructive Preference Elicitation for Multiple Users with Setwise Maxmargin Stefano Teso, Andrea Passerini, and Paolo Viappian. In Proc. International Conference on Algorithmic Decision Theory (ADT).
@inproceedings {adt17,
    author = { Teso, Stefano and Passerini, Andrea and Viappian, Paolo },
    title = "Constructive Preference Elicitation for Multiple Users with Setwise Maxmargin",
    booktitle = "Proc. International Conference on Algorithmic Decision Theory (ADT)",
    year = "2017",
    url = "papers/adt17.pdf",
}
Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning Seyed Mostafa Kia, Fabian Pedregosa, Anna Blumenthal, and Andrea Passerini. In Journal of Neuroscience Methods.
@article {Kia201797,
    author = { Kia, Seyed Mostafa and Pedregosa, Fabian and Blumenthal, Anna and Passerini, Andrea },
    title = "Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning",
    journal = "Journal of Neuroscience Methods",
    volume = "285",
    number = "",
    pages = "97 - 108",
    year = "2017",
    note = "",
    issn = "0165-0270",
    doi = "https://doi.org/10.1016/j.jneumeth.2017.05.004",
    url = "http://www.sciencedirect.com/science/article/pii/S0165027017301231",
    keywords = "MEG",
}
2016

ECML PKDD 2016 Journal Track Special Issue Thomas Gaertner, Mirco Nanni, Andrea Passerini, and Celine Robardet. In Data Mining and Knowledge Discovery 30(5).
@article {eclmpkdd_dmkd16,
    author = { Gaertner, Thomas and Nanni, Mirco and Passerini, Andrea and Robardet, Celine },
    title = "ECML PKDD 2016 Journal Track Special Issue",
    year = "2016",
    journal = "Data Mining and Knowledge Discovery",
    volume = "30",
    number = "5",
    month = "September",
    publisher = "Springer",
    url = "http://link.springer.com/journal/10618/30/5/page/1",
}
Special Issue of the ECMLPKDD 2016 Journal Track Thomas Gaertner, Mirco Nanni, Andrea Passerini, and Celine Robardet. In Machine Learning Journal 104(2-3).
@article {eclmpkdd_mlj16,
    author = { Gaertner, Thomas and Nanni, Mirco and Passerini, Andrea and Robardet, Celine },
    title = "Special Issue of the ECMLPKDD 2016 Journal Track",
    year = "2016",
    journal = "Machine Learning Journal",
    volume = "104",
    number = "2-3",
    month = "September",
    publisher = "Springer",
    url = "http://link.springer.com/journal/10994/104/2/page/1",
}
Interpretability in Linear Brain Decoding Seyed Mostafa Kia and Andrea Passerini. In ICML Workshop on Human Interpretability in Machine Learning (WHI 2016).
@inproceedings {whi2016,
    author = { Kia, Seyed Mostafa and Passerini, Andrea },
    title = "Interpretability in Linear Brain Decoding",
    booktitle = "ICML Workshop on Human Interpretability in Machine Learning (WHI 2016)",
    url = "https://arxiv.org/pdf/1606.05672.pdf",
    year = "2016",
}
Hashing-Based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report Vaishak Belle, Guy {Van den Broeck}, and Andrea Passerini. In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), Sister Conference Best Paper Track.
@inproceedings {BelleIJCAI16,
    author = { Belle, Vaishak and {Van den Broeck}, Guy and Passerini, Andrea },
    title = "Hashing-Based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report",
    booktitle = "Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), Sister Conference Best Paper Track",
    url = "papers/BelleIJCAI16.pdf",
    year = "2016",
    keywords = "conference,selected",
}
Constructive Preference Elicitation by Setwise Max-Margin Learning Stefano Teso, Andrea Passerini, and Paolo Viappiani. In Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, {IJCAI} 2016, New York, NY, USA, 9-15 July 2016.
@inproceedings {ijcai16,
    author = { Teso, Stefano and Passerini, Andrea and Viappiani, Paolo },
    title = "Constructive Preference Elicitation by Setwise Max-Margin Learning",
    booktitle = "Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, {IJCAI} 2016, New York, NY, USA, 9-15 July 2016",
    pages = "2067--2073",
    year = "2016",
    url = "papers/ijcai16.pdf",
}
Classtering: Joint Classification and Clustering with Mixture of Factor Analysers E. Sansone, A. Passerini, and F. De Natale. In Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI).
@inproceedings {ecai16,
    author = { Sansone, E. and Passerini, A. and Natale, F. De },
    title = "Classtering: Joint Classification and Clustering with Mixture of Factor Analysers",
    url = "papers/ecai16.pdf",
    booktitle = "Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI)",
    year = "2016",
}
Structured Feedback for Preference Elicitation in Complex Domains Stefano Teso, Paolo Dragone, and Andrea Passerini. In BeyondLabeler Workshop at IJCAI 2016.
@inproceedings {beyond16,
    author = { Teso, Stefano and Dragone, Paolo and Passerini, Andrea },
    title = "Structured Feedback for Preference Elicitation in Complex Domains",
    booktitle = "BeyondLabeler Workshop at IJCAI 2016",
    year = "2016",
    url = "papers/beyond16.pdf",
}
Component Caching in Hybrid Domains with Piecewise Polynomial Densities Vaishak Belle, Guy Broeck, and Andrea Passerini. In Proceedings of the 30th Conference on Artificial Intelligence (AAAI).
@inproceedings {BelleAAAI16,
    author = { Belle, Vaishak and Van den Broeck, Guy and Passerini, Andrea },
    title = "Component Caching in Hybrid Domains with Piecewise Polynomial Densities",
    booktitle = "Proceedings of the 30th Conference on Artificial Intelligence (AAAI)",
    year = "2016",
    url = "papers/aaai16.pdf",
    keywords = "conference,strong,selected",
}
RNAcommender: genome-wide recommendation of RNA-protein interactions G. Corrado, T. Tebaldi, F. Costa, P. Frasconi, and A. Passerini. In Bioinformatics.
@article {bioinfo16,
    author = { Corrado, G. and Tebaldi, T. and Costa, F. and Frasconi, P. and Passerini, A. },
    title = "RNAcommender: genome-wide recommendation of RNA-protein interactions",
    journal = "Bioinformatics",
    url = "papers/bioinfo16.pdf",
    year = "2016",
}
Constructive Layout Synthesis via Coactive Learning P. Dragone, L. Erculiani, M.T. Chietera, S. Teso, and A. Passerini. In NIPS Workshop on Constructive Machine Learning.
@inproceedings {cml2016,
    author = { Dragone, P. and Erculiani, L. and Chietera, M.T. and Teso, S. and Passerini, A. },
    title = "Constructive Layout Synthesis via Coactive Learning",
    booktitle = "NIPS Workshop on Constructive Machine Learning",
    url = "papers/cml16.pdf",
    year = "2016",
}
2015

Structured Learning Modulo Theories S. Teso, R. Sebastiani, and A. Passerini. In Artificial Intelligence Journal.
@article {aij2015,
    author = { Teso, S. and Sebastiani, R. and Passerini, A. },
    title = "Structured Learning Modulo Theories",
    journal = "Artificial Intelligence Journal",
    year = "2015",
    url = "papers/aij2015.pdf",
    optkey = "",
    optvolume = "",
    optnumber = "",
    optpages = "",
    optmonth = "",
    optnote = "accepted",
    optannote = "arXiv:1405.1675v2",
}
Inducing Sparse Programs for Learning Modulo Theories S. Teso and A. Passerini. In ICML Workshop on Constructive Machine Learning.
@inproceedings {cml2015cl,
    author = { Teso, S. and Passerini, A. },
    title = "Inducing Sparse Programs for Learning Modulo Theories",
    booktitle = "ICML Workshop on Constructive Machine Learning",
    url = "papers/cml2015cl.pdf",
    year = "2015",
}
Constructive Learning Modulo Theories S. Teso, R. Sebastiani, and A. Passerini. In ICML Workshop on Constructive Machine Learning.
@inproceedings {cml2015lmt,
    author = { Teso, S. and Sebastiani, R. and Passerini, A. },
    title = "Constructive Learning Modulo Theories",
    booktitle = "ICML Workshop on Constructive Machine Learning",
    url = "papers/cml2015lmt.pdf",
    year = "2015",
}
Bootstrapping Domain Ontologies from Wikipedia: A Uniform Approach Daniil Mirylenka, Andrea Passerini, and Luciano Serafini. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, {IJCAI} 2015, Buenos Aires, Argentina, July 25-31, 2015.
@inproceedings {DBLP:conf/ijcai/MirylenkaPS15,
    author = { Mirylenka, Daniil and Passerini, Andrea and Serafini, Luciano },
    title = "Bootstrapping Domain Ontologies from Wikipedia: {A} Uniform Approach",
    booktitle = "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, {IJCAI} 2015, Buenos Aires, Argentina, July 25-31, 2015",
    pages = "1464--1470",
    year = "2015",
    url = "papers/ijcai2015wiki.pdf",
    timestamp = "Mon, 20 Jul 2015 19:12:40 +0200",
    biburl = "http://dblp.uni-trier.de/rec/bib/conf/ijcai/MirylenkaPS15",
    bibsource = "dblp computer science bibliography, http://dblp.org",
}
Probabilistic Inference in Hybrid Domains by Weighted Model Integration Vaishak Belle, Andrea Passerini, and Guy {Van den Broeck}. In Proceedings of 24th International Joint Conference on Artificial Intelligence (IJCAI).
@inproceedings {BelleIJCAI15,
    author = { Belle, Vaishak and Passerini, Andrea and {Van den Broeck}, Guy },
    title = "Probabilistic Inference in Hybrid Domains by Weighted Model Integration",
    booktitle = "Proceedings of 24th International Joint Conference on Artificial Intelligence (IJCAI)",
    year = "2015",
    url = "papers/ijcai2015wmi.pdf",
    keywords = "conference,strong,selected",
}
Three distinct ribosome assemblies modulated by translation are the building blocks of polysomes Gabriella Viero, Lorenzo Lunelli, Andrea Passerini, Paolo Bianchini, Robert J. Gilbert, Paola Bernabo', Toma Tebaldi, Alberto Diaspro, Cecilia Pederzolli, and Alessandro Quattrone. In The Journal of Cell Biology 208(5).
@article {Viero2015,
    author = { Viero, Gabriella and Lunelli, Lorenzo and Passerini, Andrea and Bianchini, Paolo and Gilbert, Robert J. and Bernabo', Paola and Tebaldi, Toma and Diaspro, Alberto and Pederzolli, Cecilia and Quattrone, Alessandro },
    title = "Three distinct ribosome assemblies modulated by translation are the building blocks of polysomes",
    volume = "208",
    number = "5",
    pages = "581-596",
    year = "2015",
    doi = "10.1083/jcb.201406040",
    eprint = "http://jcb.rupress.org/content/208/5/581.full.pdf+html",
    url = "papers/jcb2015.pdf",
    journal = "The Journal of Cell Biology",
}
Hashing-Based Approximate Probabilistic Inference in Hybrid Domains Vaishak Belle, Guy {Van den Broeck}, and Andrea Passerini. In Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI).
@inproceedings {BelleUAI15,
    author = { Belle, Vaishak and {Van den Broeck}, Guy and Passerini, Andrea },
    title = "Hashing-Based Approximate Probabilistic Inference in Hybrid Domains",
    booktitle = "Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI)",
    url = "papers/uai2015.pdf",
    year = "2015",
    annotation = "(UAI best paper award)",
    keywords = "conference,strong,selected",
}
2014

Predicting virus mutations through statistical relational learning. Elisa Cilia, Stefano Teso, Sergio Ammendola, Tom Lenaerts, and Andrea Passerini. In BMC Bioinformatics 15(1).
@article {bmcbioinfo14_frankie,
    author = { Cilia, Elisa and Teso, Stefano and Ammendola, Sergio and Lenaerts, Tom and Passerini, Andrea },
    title = "Predicting virus mutations through statistical relational learning.",
    journal = "BMC Bioinformatics",
    year = "2014",
    volume = "15",
    pages = "309",
    number = "1",
    url = "papers/bmcbioinfo14_frankie.pdf",
    doi = "10.1186/1471-2105-15-309",
    keywords = "25238967",
    owner = "andrea",
    pii = "1471-2105-15-309",
    pmid = "25238967",
    timestamp = "2014.10.22",
}
Joint Probabilistic-Logical Refinement of Multiple Protein Feature Predictors S. Teso and A. Passerini. In BMC-Bioinformatics.
@article {bmcbioinfo14_mln,
    author = { Teso, S. and Passerini, A. },
    title = "Joint Probabilistic-Logical Refinement of Multiple Protein Feature Predictors",
    journal = "BMC-Bioinformatics",
    year = "2014",
    url = "papers/bmcbioinfo14_mln.pdf",
    volume = "15:16",
}
Improved multi-level protein-protein interaction prediction with semantic-based regularization. Claudio Sacca', Stefano Teso, Michelangelo Diligenti, and Andrea Passerini. In BMC Bioinformatics.
@article {bmcbioinformatics14_sbr,
    author = { Sacca', Claudio and Teso, Stefano and Diligenti, Michelangelo and Passerini, Andrea },
    url = "papers/bmcbioinformatics14_sbr.pdf",
    title = "Improved multi-level protein-protein interaction prediction with semantic-based regularization.",
    journal = "BMC Bioinformatics",
    year = "2014",
    volume = "15",
    pages = "103",
    doi = "10.1186/1471-2105-15-103",
    keywords = "Artificial Intelligence, Models, Molecular, Protein Binding, Protein Interaction Domains and Motifs, Proteins, Semantics, Software, 20817744",
    owner = "andrea",
    pii = "1471-2105-15-103",
    pmid = "20817744",
    timestamp = "2014.07.11",
}
PTRcombiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps. Gianluca Corrado, Toma Tebaldi, Giulio Bertamini, Fabrizio Costa, Alessandro Quattrone, Gabriella Viero, and Andrea Passerini. In BMC Genomics.
@article {bmcgenomics14,
    author = { Corrado, Gianluca and Tebaldi, Toma and Bertamini, Giulio and Costa, Fabrizio and Quattrone, Alessandro and Viero, Gabriella and Passerini, Andrea },
    title = "P{TR}combiner: mining combinatorial regulation of gene expression from post-transcriptional interaction maps.",
    journal = "BMC Genomics",
    year = "2014",
    volume = "15",
    pages = "304",
    url = "papers/bmcgenomics14.pdf",
    doi = "10.1186/1471-2164-15-304",
    keywords = "24758252",
    owner = "andrea",
    pii = "1471-2164-15-304",
    pmid = "24758252",
    timestamp = "2014.07.11",
}
Improving Activity Recognition by Segmental Pattern Mining U. Avci and A. Passerini. In IEEE Transactions on Knowledge and Data Engineering 26(4).
@article {tkde2014,
    author = { Avci, U. and Passerini, A. },
    title = "Improving Activity Recognition by Segmental Pattern Mining",
    journal = "IEEE Transactions on Knowledge and Data Engineering",
    volume = "26",
    number = "4",
    pages = "889--902",
    url = "papers/tkde2014.pdf",
    year = "2014",
}
2013

Type Extension Trees for Feature Construction and Learning in Relational Domains M. Jaeger, M. Lippi, A. Passerini, and P. Frasconi. In Artificial Intelligence Journal 204(30--55).
@article {aij13,
    author = { Jaeger, M. and Lippi, M. and Passerini, A. and Frasconi, P. },
    title = "Type Extension Trees for Feature Construction and Learning in Relational Domains",
    journal = "Artificial Intelligence Journal",
    year = "2013",
    volume = "204",
    url = "papers/aij13.pdf",
    number = "30--55",
}
Navigating the topical structure of academic search results via Wikipedia category network D. Mirylenka and A. Passerini. In ACM International Conference on Information and Knowledge Management (CIKM 2013).
@inproceedings {cikm2013,
    author = { Mirylenka, D. and Passerini, A. },
    title = "Navigating the topical structure of academic search results via Wikipedia category network",
    booktitle = "ACM International Conference on Information and Knowledge Management (CIKM 2013)",
    year = "2013",
    url = "papers/cikm2013.pdf",
    address = "San Francisco, CA, USA",
}
Supervised graph summarization for structuring academic search results D. Mirylenka and A. Passerini. In NIPS Workshop on Constructive Machine Learning.
@inproceedings {nips2013myr,
    author = { Mirylenka, D. and Passerini, A. },
    title = "Supervised graph summarization for structuring academic search results",
    booktitle = "NIPS Workshop on Constructive Machine Learning",
    url = "papers/cml2013myr.pdf",
    year = "2013",
}
Hybrid SRL with Optimization Modulo Theories S. Teso, R. Sebastiani, and A. Passerini. In NIPS Workshop on Constructive Machine Learning.
@inproceedings {nips2013teso,
    author = { Teso, S. and Sebastiani, R. and Passerini, A. },
    title = "Hybrid SRL with Optimization Modulo Theories",
    booktitle = "NIPS Workshop on Constructive Machine Learning",
    url = "papers/cml2013teso.pdf",
    year = "2013",
}
ScienScan -- an efficient visualization and browsing tool for academic search D. Mirylenka and A. Passerini. In Machine Learning and Knowledge Discovery in Databases (ECML/PKDD'13, Demo Track).
@inproceedings {ecml2013,
    author = { Mirylenka, D. and Passerini, A. },
    title = "ScienScan -- an efficient visualization and browsing tool for academic search",
    booktitle = "Machine Learning and Knowledge Discovery in Databases (ECML/PKDD'13, Demo Track)",
    year = "2013",
    url = "papers/ecml2013.pdf",
    address = "Prague, Czech Republic",
}
A Fully Unsupervised Approach to Activity Discovery U. Avci and A. Passerini. In ACM Multimedia workshop on Human Behavior Understanding (HBU 2013).
@inproceedings {hbu2013,
    author = { Avci, U. and Passerini, A. },
    title = "A Fully Unsupervised Approach to Activity Discovery",
    booktitle = "ACM Multimedia workshop on Human Behavior Understanding (HBU 2013)",
    year = "2013",
    url = "papers/hbu2013.pdf",
    address = "Barcelona, Spain",
}
Active Learning of Pareto Fronts with Disconnected Feasible Decision and Objective Spaces P. Campigotto, A. Passerini, and R. Battiti. In Metaheuristics International Conference (MIC 2013).
@inproceedings {mic2013alp,
    author = { Campigotto, P. and Passerini, A. and Battiti, R. },
    title = "Active Learning of Pareto Fronts with Disconnected Feasible Decision and Objective Spaces",
    booktitle = "Metaheuristics International Conference (MIC 2013)",
    year = "2013",
    note = "(extended abstract)",
    url = "papers/mic2013alp.pdf",
    address = "Singapore",
}
Learning to Diversify in Complex Interactive Multiobjective Optimization D. Mukhlisullina, A. Passerini, and R. Battiti. In Metaheuristics International Conference (MIC 2013).
@inproceedings {mic2013bcmoead,
    author = { Mukhlisullina, D. and Passerini, A. and Battiti, R. },
    title = "Learning to Diversify in Complex Interactive Multiobjective Optimization",
    booktitle = "Metaheuristics International Conference (MIC 2013)",
    year = "2013",
    note = "(best paper award)",
    url = "papers/mic2013bcmoead.pdf",
    address = "Singapore",
}
Kernel Methods for Structured Data Andrea Passerini. In Handbook on Neural Information Processing (Intelligent Systems Reference Library).
@inproceedings {PassHandNIP13,
    author = { Passerini, Andrea },
    year = "2013",
    isbn = "978-3-642-36656-7",
    booktitle = "Handbook on Neural Information Processing",
    volume = "49",
    series = "Intelligent Systems Reference Library",
    doi = "10.1007/978-3-642-36657-4_9",
    title = "Kernel Methods for Structured Data",
    url = "papers/nipchap.pdf",
    publisher = "Springer Berlin Heidelberg",
    pages = "283-333",
    language = "English",
}
Learning to Grow Structured Visual Summaries for Document Collections D. Mirylenka and A. Passerini. In ICML Workshop on Structured Learning: Inferring Graphs from Structured and Unstructured Inputs.
@inproceedings {slg2013,
    author = { Mirylenka, D. and Passerini, A. },
    title = "Learning to Grow Structured Visual Summaries for Document Collections",
    booktitle = "ICML Workshop on Structured Learning: Inferring Graphs from Structured and Unstructured Inputs",
    year = "2013",
    url = "papers/slg2013.pdf",
    address = "Atlanta, GA, USA",
}
Ego-Centric Graphlets for Personality and Affective States Recognition S. Teso, J. Staiano, B. Lepri, A. Passerini, and F. Pianesi. In ASE/IEEE International Conference on Social Computing.
@inproceedings {soccom2013,
    author = { Teso, S. and Staiano, J. and Lepri, B. and Passerini, A. and Pianesi, F. },
    title = "Ego-Centric Graphlets for Personality and Affective States Recognition",
    booktitle = "ASE/IEEE International Conference on Social Computing",
    year = "2013",
    url = "papers/soccom2013.pdf",
    address = "Washington D.C., USA",
}
Active learning of Pareto fronts P. Campigotto, A. Passerini, and R. Battiti. In IEEE Transactions on Neural Networks and Learning Systems 25(3).
@article {tnn2013,
    author = { Campigotto, P. and Passerini, A. and Battiti, R. },
    title = "Active learning of Pareto fronts",
    journal = "IEEE Transactions on Neural Networks and Learning Systems",
    year = "2013",
    volume = "25",
    number = "3",
    url = "papers/tnn2013.pdf",
    pages = "506--519",
}
Ego-Centric Graphlets for Personality and Affective States Recognition S. Teso, J. Staiano, B. Lepri, A. Passerini, and F. Pianesi. In Workshop on Information in Networks (WIN 2013).
@inproceedings {win2013,
    author = { Teso, S. and Staiano, J. and Lepri, B. and Passerini, A. and Pianesi, F. },
    title = "Ego-Centric Graphlets for Personality and Affective States Recognition",
    booktitle = "Workshop on Information in Networks (WIN 2013)",
    year = "2013",
    url = "papers/win2013.pdf",
    note = "(abstract)",
}
2012

Predicting Metal-Binding Sites from Protein Sequence Andrea Passerini, Marco Lippi, and Paolo Frasconi. In IEEE/ACM Trans. Comput. Biol. Bioinformatics.
@article {ieeetccb11,
    author = { Passerini, Andrea and Lippi, Marco and Frasconi, Paolo },
    title = "Predicting Metal-Binding Sites from Protein Sequence",
    journal = "IEEE/ACM Trans. Comput. Biol. Bioinformatics",
    issue_date = "January 2012",
    volume = "9",
    issue = "1",
    month = "January",
    year = "2012",
    issn = "1545-5963",
    pages = "203--213",
    numpages = "11",
    doi = "http://dx.doi.org/10.1109/TCBB.2011.94",
    acmid = "2077958",
    publisher = "IEEE Computer Society Press",
    address = "Los Alamitos, CA, USA",
    url = "papers/ieeetccb11.pdf",
    keywords = "Metal-binding prediction, machine learning, structured-output learning, greedy algorithms.",
}
Predicting virus mutations through relational learning Elisa Cilia, Stefano Teso, Sergio Ammendola, Tom Lenaerts, and Andrea Passerini. In ECCB Workshop on Annotation, Interpretation and Management of Mutations (AIMM-2012).
@inproceedings {aimm12,
    author = { Cilia, Elisa and Teso, Stefano and Ammendola, Sergio and Lenaerts, Tom and Passerini, Andrea },
    title = "Predicting virus mutations through relational learning",
    booktitle = "ECCB Workshop on Annotation, Interpretation and Management of Mutations (AIMM-2012)",
    year = "2012",
    url = "papers/aimm12.pdf",
    bibsource = "DBLP, http://dblp.uni-trier.de",
}
Widespread translational control uncouples transcriptome and translatome profiles in mammalian cells T. Tebaldi, A. Re, G. Viero, I. Pegoretti, A. Passerini, E. Blanzieri, and A. Quattrone. In BMC Genomics.
@article {bmcgenomics12,
    author = { Tebaldi, T. and Re, A. and Viero, G. and Pegoretti, I. and Passerini, A. and Blanzieri, E. and Quattrone, A. },
    title = "Widespread translational control uncouples transcriptome and translatome profiles in mammalian cells",
    journal = "BMC Genomics",
    year = "2012",
    volume = "13:220",
    url = "papers/bmcgenomics12.pdf",
    optnumber = "",
    optpages = "",
    optmonth = "",
    optnote = "",
    optannote = "",
}
Metal binding in proteins: machine learning complements X-ray absorption spectroscopy M. Lippi, A. Passerini, M. Punta, and P. Frasconi. In Machine Learning and Knowledge Discovery in Databases (ECML/PKDD'12, Nectar Track) (Lecture Notes in Computer Science).
@inproceedings {nectar12,
    author = { Lippi, M. and Passerini, A. and Punta, M. and Frasconi, P. },
    title = "Metal binding in proteins: machine learning complements X-ray absorption spectroscopy",
    doi = "10.1007/978-3-642-33486-3_63",
    publisher = "Springer Berlin Heidelberg",
    isbn = "978-3-642-33485-6",
    booktitle = "Machine Learning and Knowledge Discovery in Databases (ECML/PKDD'12, Nectar Track)",
    volume = "7524",
    series = "Lecture Notes in Computer Science",
    url = "papers/nectar12.pdf",
    year = "2012",
}
Improving Activity Recognition by Segmental Pattern Mining U. Avci and A. Passerini. In PerCOM'2012 Workshop on PervasivE Learning, Life, and Leisure.
@inproceedings {perel012,
    author = { Avci, U. and Passerini, A. },
    title = "Improving Activity Recognition by Segmental Pattern Mining",
    booktitle = "PerCOM'2012 Workshop on PervasivE Learning, Life, and Leisure",
    url = "papers/perel012.pdf",
    year = "2012",
}
2011

Relational Feature Mining with Hierarchical Multitask kFOIL Elisa Cilia, Neils Landwehr, and Andrea Passerini. In Fundamenta Informaticae 113(2).
@article {fundinf11,
    author = { Cilia, Elisa and Landwehr, Neils and Passerini, Andrea },
    title = "Relational Feature Mining with Hierarchical Multitask kFOIL",
    journal = "Fundamenta Informaticae",
    month = "December",
    year = "2011",
    volume = "113",
    number = "2",
    url = "papers/fundinf11.pdf",
    pages = "151--177",
}
Preference elicitation for interactive learning of Optimization Modulo Theory problems P. Campigotto, A. Passerini, and R. Battiti. In NIPS'11 workshop on Choice Models and Preference Learning.
@inproceedings {cmpl11,
    author = { Campigotto, P. and Passerini, A. and Battiti, R. },
    title = "Preference elicitation for interactive learning of Optimization Modulo Theory problems",
    booktitle = "NIPS'11 workshop on Choice Models and Preference Learning",
    url = "papers/cmpl11.pdf",
    year = "2011",
}
Characterization of metalloproteins by high-throughput X-ray absorption spectroscopy. W. Shi, M. Punta, J. Bohon, J.M. Sauder, R. D'Mello, M. Sullivan, J. Toomey, D. Abel, M. Lippi, A. Passerini, P. Frasconi, S.K. Burley, B. Rost, and M.R. Chance. In Genome Res 21(6).
@article {genomeres11,
    author = { Shi, W. and Punta, M. and Bohon, J. and Sauder, J.M. and D'Mello, R. and Sullivan, M. and Toomey, J. and Abel, D. and Lippi, M. and Passerini, A. and Frasconi, P. and Burley, S.K. and Rost, B. and Chance, M.R. },
    title = "Characterization of metalloproteins by high-throughput X-ray absorption spectroscopy.",
    journal = "Genome Res",
    volume = "21",
    number = "6",
    pages = "898-907",
    year = "2011",
    url = "papers/genomeres11.pdf",
}
Active Learning of Combinatorial Features for Interactive Optimization Paolo Campigotto, Andrea Passerini, and Roberto Battiti. In Proceedings of the 5th international conference on Learning and Intelligent Optimization.
@inproceedings {lion11,
    author = { Campigotto, Paolo and Passerini, Andrea and Battiti, Roberto },
    title = "Active Learning of Combinatorial Features for Interactive Optimization",
    booktitle = "Proceedings of the 5th international conference on Learning and Intelligent Optimization",
    year = "2011",
    url = "papers/lion11.pdf",
    pages = "336-350",
}
Relational information gain M. Lippi, M. Jaeger, P. Frasconi, and A. Passerini. In Machine Learning.
@article {mlj11,
    author = { Lippi, M. and Jaeger, M. and Frasconi, P. and Passerini, A. },
    title = "Relational information gain",
    journal = "Machine Learning",
    volume = "83",
    url = "papers/mlj11.pdf",
    pages = "219--239",
    year = "2011",
}
MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence. A. Passerini, M. Lippi, and P. Frasconi. In Nucleic Acids Res 39(Web Server issue).
@article {nar11,
    author = { Passerini, A. and Lippi, M. and Frasconi, P. },
    title = "MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence.",
    journal = "Nucleic Acids Res",
    volume = "39",
    url = "papers/nar11.pdf",
    number = "Web Server issue",
    pages = "W288-92",
    year = "2011",
}
2010

Predicting structural and functional sites in proteins by searching for maximum-weight cliques F. Mascia, E. Cilia, M. Brunato, and A. Passerini. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10).
@inproceedings {aaai10,
    author = { Mascia, F. and Cilia, E. and Brunato, M. and Passerini, A. },
    title = "Predicting structural and functional sites in proteins by searching for maximum-weight cliques",
    booktitle = "Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI-10)",
    url = "papers/aaai10.pdf",
    year = "2010",
}
Frankenstein Junior: a relational learning approach toward protein engineering E. Cilia and A. Passerini. In ECCB 2010 Workshop on Annotation, Interpretation, and Management of Mutations (AIMM 2010).
@inproceedings {aimm10,
    author = { Cilia, E. and Passerini, A. },
    title = "Frankenstein Junior: a relational learning approach toward protein engineering",
    booktitle = "ECCB 2010 Workshop on Annotation, Interpretation, and Management of Mutations (AIMM 2010)",
    year = "2010",
    url = "papers/aimm10.pdf",
    address = "Ghent (Belgium)",
}
Automatic prediction of catalytic residues by modeling residue structural neighborhood Elisa Cilia and Andrea Passerini. In BMC Bioinformatics 11(1).
@article {bmc10,
    author = { Cilia, Elisa and Passerini, Andrea },
    title = "Automatic prediction of catalytic residues by modeling residue structural neighborhood",
    journal = "BMC Bioinformatics",
    volume = "11",
    year = "2010",
    number = "1",
    pages = "115",
    url = "papers/bmc10.pdf",
    doi = "10.1186/1471-2105-11-115",
}
Handling concept drift in preference learning for interactive decision making P. Campigotto, A. Passerini, and R. Battiti. In ECML/PKDD 2010 Workshop on Handling Concept Drift in Adaptive Information Systems (HaCDAIS 2010).
@inproceedings {hacdais10,
    author = { Campigotto, P. and Passerini, A. and Battiti, R. },
    title = "Handling concept drift in preference learning for interactive decision making",
    booktitle = "ECML/PKDD 2010 Workshop on Handling Concept Drift in Adaptive Information Systems (HaCDAIS 2010)",
    year = "2010",
    url = "papers/hacdais10.pdf",
    address = "Barcelona (Spain)",
}
From on-going to complete activity recognition exploiting related activities C. Nicolini, B. Lepri, S. Teso, and A. Passerini. In International Workshop on Human Behavour Understanding (HBU'10).
@inproceedings {hbu10,
    author = { Nicolini, C. and Lepri, B. and Teso, S. and Passerini, A. },
    title = "From on-going to complete activity recognition exploiting related activities",
    booktitle = "International Workshop on Human Behavour Understanding (HBU'10)",
    url = "papers/hbu10.pdf",
    year = "2010",
}
Adapting to a realistic decision maker: experiments towards a reactive multi-objective optimizer P. Campigotto and A. Passerini. In LION workshop on Multiobjective Metaheuristics (LION-MOME).
@inproceedings {lion-mome10,
    author = { Campigotto, P. and Passerini, A. },
    title = "Adapting to a realistic decision maker: experiments towards a reactive multi-objective optimizer",
    booktitle = "LION workshop on Multiobjective Metaheuristics (LION-MOME)",
    url = "papers/lion-mome10.pdf",
    year = "2010",
}
Fast learning of relational kernels N. Landwehr, A. Passerini, L. {De Raedt}, and P. Frasconi. In Machine Learning 79(3).
@article {mlj10,
    author = { Landwehr, N. and Passerini, A. and {De Raedt}, L. and Frasconi, P. },
    title = "Fast learning of relational kernels",
    journal = "Machine Learning",
    pages = "305--342",
    url = "papers/mlj10.pdf",
    publisher = "Springer",
    volume = "79",
    number = "3",
    year = "2010",
    doi = "10.1007/s10994-009-5163-1",
}
An On/Off Lattice Approach to Protein Structure Prediction from Contact Maps S. Teso, C. Di Risio, A. Passerini, and R. Battiti. In Proceedings of Pattern Recognition in Bioinformatics (PRIB2010) (Lecture Notes in Bioinformatics (LNBI)).
@inproceedings {prib10,
    author = { Teso, S. and Risio, C. Di and Passerini, A. and Battiti, R. },
    title = "An On/Off Lattice Approach to Protein Structure Prediction from Contact Maps",
    booktitle = "Proceedings of Pattern Recognition in Bioinformatics (PRIB2010)",
    year = "2010",
    series = "Lecture Notes in Bioinformatics (LNBI)",
    url = "papers/prib10.pdf",
    publisher = "Springer",
}
Brain-Computer Evolutionary Multi-Objective Optimization (BC-EMO): a genetic algorithm adapting to the decision maker R. Battiti and A. Passerini. In IEEE Transactions on Evolutionary Computation.
@article {tevo10,
    author = { Battiti, R. and Passerini, A. },
    title = "Brain-Computer Evolutionary Multi-Objective Optimization (BC-EMO): a genetic algorithm adapting to the decision maker",
    journal = "IEEE Transactions on Evolutionary Computation",
    url = "papers/tevo10.pdf",
    year = "2010",
}
For publications prior to 2010 please check the authors' webpages.