The fourth stream of invited sessions on "Preference Learning" has been organized at the European Conference on Operational Research (EURO 2013) in Rome, Italy, July 1-4, 2013.

With these invited sessions we try to bring together researchers that have been working on preference learning and related research topics in operations research, machine learning, multicriteria decision making, preference modeling, data mining and statistics.

The EURO conference offers the perfect forum for that, since it always attracts thousands of participants with diverse backgrounds in operational research.

The original call for papers can be found here.

The stream of "Preference Learning" sessions is sponsored by the EURO Working Group on Multicriteria Decision Aiding.

See also:

• Special Issue in Machine Learning Journal on Preference Learning and Ranking
• Dagstuhl Seminar on Preference Learning

Organizers:

Krzysztof Dembczynski, Poznan University of Technology
Roman Slowinski, Poznan University of Technology
Willem Waegeman, Ghent University

Presentations in the Preference Learning Stream:

• Krzysztof Dembczynski, Roman Slowinski, Willem Waegeman: Preference Learning from Different Perspectives [pdf] [pdf]
• Tommi Tervonen, Milosz Kadzinski: Multiple criteria ranking with additive value models and holistic pair-wise preference statements [pdf]
• Paolo Viappiani, Patrice Perny, Christophe Gonzales: Elicitation of Non-linear Utility Models [pdf]
• Nicolas Vayatis: New perspectives on the problem of learning how to order high dimensional data [pdf]
• Michael Rademaker, Bernard De Baets: A ranking rule and its relation to the feedback edge set problem in a stochastic monotonicity setting
• Gert van Valkenhoef, Tommi Tervonen: Optimal weight constraint elicitation techniques for additive multi-attribute utility models [pdf]
• Roman Slowinski, Salvatore Greco, Vincent Mousseau: Inferring parsimonious preference models in robust ordinal regression [pdf]
• Eric Sibony, Stephan Clémençon, Jeremie Jakubowicz: Wavelet-based methods for ranking
• Claudio Gentile: Multilabel Classification and Ranking with Partial Feedback [pdf]
• Tapio Pahikkala: Kernel-Based Learning of Conditional Utility Functions
• Eyke Hüllermeier: Preference-based Racing Algorithms
• Olivier Sobrie, Vincent Mousseau, Marc Pirlot: Learning the parameters of a multiple criteria sorting method from large sets of assignemnt examples [pdf]
• Salvatore Corrente, Silvia Angilella, Salvatore Greco, Roman Slowinski: Robust Ordinal Regression and SMAA in Multiple Criteria Hierarchy Process for the Choquet Integral [pdf]
• Massimo Gurrieri, Philippe Fortemps, Xavier Siebert: Label Ranking with Intensity of Preference
• Salvatore Greco, Benedetto Matarazzo, Roman Slowinski: New developments of Interactive Multiobjective Optimization using Dominance-based Rough Set Approach
• Ori Davidov: Improving ranking using order restrictions
• Frédéric Borzee, Vincent Mousseau, Marc Pirlot, Xavier Siebert, Paolo Viappiani: Bayesian Recommendations and Utility Elicitation with Intensity of Preference Statements
• Peter Vojtas, Alan Eckhardt, Ladislav Peska: Implicit feedback and personalization in a web shop [pdf]
• Willem Waegeman: Recommender Systems: From Academic Research to Industrial Practice