LAMSADE
Viappiani Paolo
Chargé de recherche CNRS
Biographie
Paolo Viappiani is a CNRS researcher since 2012, affiliated with LIP6 (Sorbonne Université) until September 2021, and since then affiliated with LAMSADE (Université Paris Dauphine). He holds an engineering diploma from Politecnico di Milano and a PhD in Computer Science from EPFL.
His research interests span algorithmic decision theory, artificial intelligence, recommender systems.
Publications
Articles
Viappiani P. (2024), Volumetric Aggregation Methods for Scoring Rules with Unknown Weights, Group Decision and Negotiation, vol. 33, p. 515–563 
Vandeputte J., Herold P., Kuslii M., Viappiani P., Muller L., Martin C., Davidenko O., Delaere F., Manfredotti C., Cornuéjols A., Darcel N. (2023), Principles and Validations of an Artificial Intelligence-Based Recommender System Suggesting Acceptable Food Changes, The Journal of Nutrition, vol. 153, n°2, p. 598-604
Communications avec actes
Jacquet N., Guigue V., Manfredotti C., Saïs F., Dervaux S., Viappiani P. (2024), Modélisation du caractère séquentiel des repas pour améliorer la performance d'un système de recommandation alimentaire, in Jérôme Gensel ; Christophe Cruz ; Hocine Cherif, Editions RNTI, 131-142 p.
Bronzini M., Robbi E., Viappiani P., Passerini A. (2023), Environmentally-Aware Bundle Recommendation Using the Choquet Integral, in Kobi Gal . Ann Nowé ; Grzegorz J. Nalepa ; Roy Fairstein ; Roxana Rădulescu, Amsterdam, IOS Press, 3182-3189 p.
Pourkhajouei S., Toffano F., Viappiani P., Wilson N. (2023), An Efficient Non-Bayesian Approach for Interactive Preference Elicitation Under Noisy Preference Models, in Zied Bouraoui ; Srdjan Vesic, Berlin Heidelberg, Springer International Publishing, 308-321 p.
Konieczny S., Moretti S., Ravier A., Viappiani P. (2022), Selecting the Most Relevant Elements from a Ranking over Sets, in Florence Dupin de Saint-Cyr, Meltem Öztürk-Escoffier, Nico Potyka, Springer, 172-185 p.
Napolitano B., Cailloux O., Viappiani P. (2021), Simultaneous Elicitation of Scoring Rule and Agent Preferences for Robust Winner Determination, in Dimitris Fotakis, David Ríos Insua, Springer, 51-67 p.
Prépublications / Cahiers de recherche
Jacquet N., Manfredotti C., Guigue V., Saïs F., Viappiani P. (2023), An EXplainable RecommandER SYStem for the Nutrition Domain, combining Knowledge Graphs and Machine Learning, Paris, Preprint Lamsade