Paolo Viappiani

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 29

Top Topics

Preference Elicitation

Choquet Integral

Top Venues

Publications

Giovanni De Toni, Paolo Viappiani, Stefano Teso, Bruno Lepri, Andrea Passerini
Personalized Algorithmic Recourse with Preference Elicitation. Trans. Mach. Learn. Res. 2024 (2024)
Erich Robbi, Marco Bronzini, Paolo Viappiani, Andrea Passerini
Personalized bundle recommendation using preference elicitation and the Choquet integral. Frontiers Artif. Intell. 7 (2024)
Marco Bronzini, Erich Robbi, Paolo Viappiani, Andrea Passerini
Environmentally-Aware Bundle Recommendation Using the Choquet Integral. ECAI (2023)
Samira Pourkhajouei, Federico Toffano, Paolo Viappiani, Nic Wilson
An Efficient Non-Bayesian Approach for Interactive Preference Elicitation Under Noisy Preference Models. ECSQARU (2023)
Giovanni De Toni, Paolo Viappiani, Bruno Lepri, Andrea Passerini
Generating personalized counterfactual interventions for algorithmic recourse by eliciting user preferences. CoRR (2022)
Sébastien Konieczny, Stefano Moretti, Ariane Ravier, Paolo Viappiani
Selecting the Most Relevant Elements from a Ranking over Sets. SUM (2022)
Arnaud Grivet Sébert, Nicolas Maudet, Patrice Perny, Paolo Viappiani
Preference Aggregation in the Generalised Unavailable Candidate Model. ADT (2021)
Cristina E. Manfredotti, Paolo Viappiani
A Bayesian Interpretation of the Monty Hall Problem with Epistemic Uncertainty. MDAI (2021)
Beatrice Napolitano, Olivier Cailloux, Paolo Viappiani
Simultaneous Elicitation of Scoring Rule and Agent Preferences for Robust Winner Determination. ADT (2021)
Federico Toffano, Paolo Viappiani, Nic Wilson
Efficient Exact Computation of Setwise Minimax Regret for Interactive Preference Elicitation. AAMAS (2021)
Arnaud Grivet Sébert, Nicolas Maudet, Patrice Perny, Paolo Viappiani
Rank Aggregation by Dissatisfaction Minimisation in the Unavailable Candidate Model. AAMAS (2021)
Paolo Viappiani, Craig Boutilier
On the equivalence of optimal recommendation sets and myopically optimal query sets. Artif. Intell. 286 (2020)
Agnès Rico, Paolo Viappiani
Incremental Elicitation of Capacities for the Sugeno Integral with a Maximin Approach. SUM (2020)
Ons Nefla, Imène Brigui, Meltem Öztürk, Paolo Viappiani, Oussama Raboun
Agent-based ordinal classification for group decision making. WI/IAT (2020)
Ons Nefla, Meltem Öztürk, Paolo Viappiani, Imène Brigui-Chtioui
Interactive Elicitation of a Majority Rule Sorting Model with Maximum Margin Optimization. ADT (2019)
Beatrice Napolitano, Olivier Cailloux, Paolo Viappiani
Simultaneous Elicitation of Committee and Voters' Preferences. RJCIA (2019)
Paolo Viappiani
Positional Scoring Rules with Uncertain Weights. SUM (2018)
Hugo Gilbert, Nawal Benabbou, Patrice Perny, Olivier Spanjaard, Paolo Viappiani
Incremental Decision Making Under Risk with the Weighted Expected Utility Model. IJCAI (2017)
Nawal Benabbou, Patrice Perny, Paolo Viappiani
Incremental elicitation of Choquet capacities for multicriteria choice, ranking and sorting problems. Artif. Intell. 246 (2017)
Stefano Teso, Andrea Passerini, Paolo Viappiani
Constructive Preference Elicitation for Multiple Users with Setwise Max-margin. ADT (2017)
Patrice Perny, Paolo Viappiani, Abdellah Boukhatem
Incremental Preference Elicitation for Decision Making Under Risk with the Rank-Dependent Utility Model. UAI (2016)
Nawal Benabbou, Serena Di Sabatino Di Diodoro, Patrice Perny, Paolo Viappiani
Incremental Preference Elicitation in Multi-attribute Domains for Choice and Ranking with the Borda Count. SUM (2016)
Stefano Teso, Andrea Passerini, Paolo Viappiani
Constructive Preference Elicitation by Setwise Max-margin Learning. CoRR (2016)
Hugo Gilbert, Bruno Zanuttini, Paul Weng, Paolo Viappiani, Esther Nicart
Model-Free Reinforcement Learning with Skew-Symmetric Bilinear Utilities. UAI (2016)
Gabriella Pigozzi, Alexis Tsoukiàs, Paolo Viappiani
Preferences in artificial intelligence. Ann. Math. Artif. Intell. 77 (3-4) (2016)
Stefano Teso, Andrea Passerini, Paolo Viappiani
Constructive Preference Elicitation by Setwise Max-Margin Learning. IJCAI (2016)
Hugo Gilbert, Olivier Spanjaard, Paolo Viappiani, Paul Weng
Reducing the Number of Queries in Interactive Value Iteration. ADT (2015)
Hugo Gilbert, Olivier Spanjaard, Paolo Viappiani, Paul Weng
Solving MDPs with Skew Symmetric Bilinear Utility Functions. IJCAI (2015)
Paolo Viappiani
Characterization of Scoring Rules with Distances: Application to the Clustering of Rankings. IJCAI (2015)
Paolo Viappiani
Aggregation of Uncertain Qualitative Preferences for a Group of Agents. IPMU (2) (2014)
Nawal Benabbou, Patrice Perny, Paolo Viappiani
Incremental Elicitation of Choquet Capacities for Multicriteria Decision Making. ECAI (2014)
Paolo Viappiani
Preference Modeling and Preference Elicitation: An Overview. DMRS (2014)
Paolo Viappiani, Christian Kroer
Robust Optimization of Recommendation Sets with the Maximin Utility Criterion. ADT (2013)
Paolo Viappiani
Thompson Sampling for Bayesian Bandits with Resets. ADT (2013)
Alexis Tsoukiàs, Paolo Viappiani
Tutorial on preference handling. RecSys (2013)
Paolo Viappiani
Monte Carlo Methods for Preference Learning. LION (2012)
Boi Faltings, Pearl Pu, Paolo Viappiani
Preference-based Search using Example-Critiquing with Suggestions CoRR (2011)
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton, Craig Boutilier
Learning Complex Concepts Using Crowdsourcing: A Bayesian Approach. ADT (2011)
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton, Craig Boutilier
A Bayesian Concept Learning Approach to Crowdsourcing. Interactive Decision Theory and Game Theory (2011)
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton, Craig Boutilier
A Bayesian Concept Learning Approach to Crowdsourcing. ITWP@IJCAI (2011)
Paolo Viappiani, Craig Boutilier
Recommendation Sets and Choice Queries: There Is No Exploration/Exploitation Tradeoff! AAAI (2011)
Craig Boutilier, Kevin Regan, Paolo Viappiani
Simultaneous Elicitation of Preference Features and Utility. AAAI (2010)
Paolo Viappiani, Craig Boutilier
Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets. NIPS (2010)
Craig Boutilier, Kevin Regan, Paolo Viappiani
Preference elicitation with subjective features. RecSys (2009)
Paolo Viappiani, Craig Boutilier
Optimal Set Recommendations Based on Regret. ITWP (2009)
Paolo Viappiani, Craig Boutilier
Regret-based optimal recommendation sets in conversational recommender systems. RecSys (2009)
Craig Boutilier, Kevin Regan, Paolo Viappiani
Online feature elicitation in interactive optimization. ICML (2009)
Bart Peintner, Paolo Viappiani, Neil Yorke-Smith
Preferences in Interactive Systems: Technical Challenges and Case Studies. AI Mag. 29 (4) (2008)
Paolo Viappiani, Pearl Pu, Boi Faltings
Preference-based search with adaptive recommendations. AI Commun. 21 (2-3) (2008)
Paolo Viappiani, Pearl Pu, Boi Faltings
Conversational recommenders with adaptive suggestions. RecSys (2007)
Paolo Viappiani, Boi Faltings, Pearl Pu
Evaluating Preference-based Search Tools: A Tale of Two Approaches. AAAI (2006)
Paolo Viappiani, Boi Faltings
Implementing example-based tools for preference-based search. ICWE (2006)
Pearl Pu, Paolo Viappiani, Boi Faltings
Increasing user decision accuracy using suggestions. CHI (2006)
Paolo Viappiani, Boi Faltings
Design and Implementation of Preference-Based Search. WISE (2006)
Paolo Viappiani, Boi Faltings, Pearl Pu
Preference-based Search using Example-Critiquing with Suggestions. J. Artif. Intell. Res. 27 (2006)
Paolo Viappiani, Boi Faltings, Pearl Pu
The Lookahead Principle for Preference Elicitation: Experimental Results. FQAS (2006)
Boi Faltings, Pearl Pu, Marc Torrens, Paolo Viappiani
Designing example-critiquing interaction. IUI (2004)