Perchet, Vianney

81 publications

NeurIPS 2025 Comparing Uniform Price and Discriminatory Multi-Unit Auctions Through Regret Minimization Marius Potfer, Vianney Perchet

ICLR 2025 Feature-Based Online Bilateral Trade Solenne Gaucher, Martino Bernasconi, Matteo Castiglioni, Andrea Celli, Vianney Perchet

AISTATS 2025 On Tradeoffs in Learning-Augmented Algorithms Ziyad Benomar, Vianney Perchet

ICML 2025 Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search Ziyad Benomar, Lorenzo Croissant, Vianney Perchet, Spyros Angelopoulos

NeurIPS 2025 Stable Matching with Ties: Approximation Ratios and Learning Shiyun Lin, Simon Mauras, Nadav Merlis, Vianney Perchet

ICML 2025 The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback Côme Fiegel, Pierre Menard, Tadashi Kozuno, Michal Valko, Vianney Perchet

NeurIPS 2025 The Price of Opportunity Fairness in Matroid Allocation Problems Rémi Castera, Felipe Garrido, Patrick Loiseau, Simon Mauras, Mathieu Molina, Vianney Perchet

JMLR 2024 A Survey on Multi-Player Bandits Etienne Boursier, Vianney Perchet

ICML 2024 Active Ranking and Matchmaking, with Perfect Matchings Hafedh El Ferchichi, Matthieu Lerasle, Vianney Perchet

NeurIPS 2024 Addressing Bias in Online Selection with Limited Budget of Comparisons Ziyad Benomar, Evgenii Chzhen, Nicolas Schreuder, Vianney Perchet

AISTATS 2024 Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication Hugo Richard, Etienne Boursier, Vianney Perchet

NeurIPS 2024 DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation Felipe Garrido-Lucero, Benjamin Heymann, Maxime Vono, Patrick Loiseau, Vianney Perchet

NeurIPS 2024 Improved Algorithms for Contextual Dynamic Pricing Matilde Tullii, Solenne Gaucher, Nadav Merlis, Vianney Perchet

ICMLW 2024 Improved Algorithms for Contextual Dynamic Pricing Matilde Tullii, Solenne Gaucher, Nadav Merlis, Vianney Perchet

NeurIPS 2024 Improved Learning Rates in Multi-Unit Uniform Price Auctions Marius Potfer, Dorian Baudry, Hugo Richard, Vianney Perchet, Cheng Wan

NeurIPS 2024 Local and Adaptive Mirror Descents in Extensive-Form Games Côme Fiegel, Pierre Ménard, Tadashi Kozuno, Rémi Munos, Vianney Perchet, Michal Valko

NeurIPS 2024 Lookback Prophet Inequalities Ziyad Benomar, Dorian Baudry, Vianney Perchet

COLT 2024 Mode Estimation with Partial Feedback Charles Arnal, Vivien Cabannes, Vianney Perchet

AISTATS 2024 Multi-Armed Bandits with Guaranteed Revenue per Arm Dorian Baudry, Nadav Merlis, Mathieu Benjamin Molina, Hugo Richard, Vianney Perchet

ICML 2024 Non-Clairvoyant Scheduling with Partial Predictions Ziyad Benomar, Vianney Perchet

NeurIPS 2024 Optimizing the Coalition Gain in Online Auctions with Greedy Structured Bandits Dorian Baudry, Hugo Richard, Maria Cherifa, Clément Calauzènes, Vianney Perchet

NeurIPS 2024 Strategic Multi-Armed Bandit Problems Under Debt-Free Reporting Ahmed Ben Yahmed, Clément Calauzènes, Vianney Perchet

NeurIPS 2024 The Value of Reward Lookahead in Reinforcement Learning Nadav Merlis, Dorian Baudry, Vianney Perchet

ICMLW 2024 The Value of Reward Lookahead in Reinforcement Learning Nadav Merlis, Dorian Baudry, Vianney Perchet

ICML 2023 Adapting to Game Trees in Zero-Sum Imperfect Information Games Côme Fiegel, Pierre Menard, Tadashi Kozuno, Remi Munos, Vianney Perchet, Michal Valko

NeurIPS 2023 Advice Querying Under Budget Constraint for Online Algorithms Ziyad Benomar, Vianney Perchet

ICML 2023 On Preemption and Learning in Stochastic Scheduling Nadav Merlis, Hugo Richard, Flore Sentenac, Corentin Odic, Mathieu Molina, Vianney Perchet

AISTATS 2023 Stochastic Mirror Descent for Large-Scale Sparse Recovery Sasila Ilandarideva, Yannis Bekri, Anatoli Iouditski, Vianney Perchet

NeurIPS 2023 Trading-Off Price for Data Quality to Achieve Fair Online Allocation Mathieu Molina, Nicolas Gast, Patrick Loiseau, Vianney Perchet

AISTATS 2022 Encrypted Linear Contextual Bandit Evrard Garcelon, Matteo Pirotta, Vianney Perchet

NeurIPS 2022 Active Labeling: Streaming Stochastic Gradients Vivien Cabannes, Francis R. Bach, Vianney Perchet, Alessandro Rudi

FnTML 2022 Learning in Repeated Auctions Thomas Nedelec, Clément Calauzènes, Noureddine El Karoui, Vianney Perchet

ALT 2022 Privacy Amplification via Shuffling for Linear Contextual Bandits Evrard Garcelon, Kamalika Chaudhuri, Vianney Perchet, Matteo Pirotta

ALT 2022 Social Learning in Non-Stationary Environments Etienne Boursier, Vianney Perchet, Marco Scarsini

NeurIPS 2021 Decentralized Learning in Online Queuing Systems Flore Sentenac, Etienne Boursier, Vianney Perchet

NeurIPS 2021 Local Differential Privacy for Regret Minimization in Reinforcement Learning Evrard Garcelon, Vianney Perchet, Ciara Pike-Burke, Matteo Pirotta

NeurIPS 2021 Making the Most of Your Day: Online Learning for Optimal Allocation of Time Etienne Boursier, Tristan Garrec, Vianney Perchet, Marco Scarsini

ICML 2021 Online A-Optimal Design and Active Linear Regression Xavier Fontaine, Pierre Perrault, Michal Valko, Vianney Perchet

NeurIPS 2021 Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm Nathan Noiry, Vianney Perchet, Flore Sentenac

NeurIPS 2021 Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits Reda Ouhamma, Rémy Degenne, Pierre Gaillard, Vianney Perchet

ICML 2021 Pure Exploration and Regret Minimization in Matching Bandits Flore Sentenac, Jialin Yi, Clement Calauzenes, Vianney Perchet, Milan Vojnovic

NeurIPS 2021 ROI Maximization in Stochastic Online Decision-Making Nicolò Cesa-Bianchi, Tom Cesari, Yishay Mansour, Vianney Perchet

NeurIPS 2021 Stochastic Online Linear Regression: The Forward Algorithm to Replace Ridge Reda Ouhamma, Odalric-Ambrym Maillard, Vianney Perchet

AISTATS 2020 A Practical Algorithm for Multiplayer Bandits When Arm Means Vary Among Players Abbas Mehrabian, Etienne Boursier, Emilie Kaufmann, Vianney Perchet

ALT 2020 An Adaptive Stochastic Optimization Algorithm for Resource Allocation Xavier Fontaine, Shie Mannor, Vianney Perchet

COLT 2020 Covariance-Adapting Algorithm for Semi-Bandits with Application to Sparse Outcomes Pierre Perrault, Michal Valko, Vianney Perchet

ALT 2020 Finding Robust Nash Equilibria Vianney Perchet

AISTATS 2020 Robust Stackelberg Buyers in Repeated Auctions Thomas Nedelec, Clement Calauzenes, Vianney Perchet, Noureddine El Karoui

NeurIPS 2020 Robustness of Community Detection to Random Geometric Perturbations Sandrine Peche, Vianney Perchet

COLT 2020 Selfish Robustness and Equilibria in Multi-Player Bandits Etienne Boursier, Vianney Perchet

NeurIPS 2020 Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits Pierre Perrault, Etienne Boursier, Michal Valko, Vianney Perchet

AISTATS 2020 Utility/Privacy Trade-Off Through the Lens of Optimal Transport Etienne Boursier, Vianney Perchet

AISTATS 2019 Bridging the Gap Between Regret Minimization and Best Arm Identification, with Application to A/B Tests Rémy Degenne, Thomas Nedelec, Clement Calauzenes, Vianney Perchet

NeurIPS 2019 Categorized Bandits Matthieu Jedor, Vianney Perchet, Jonathan Louedec

ALT 2019 Dynamic Pricing with Finitely Many Unknown Valuations Nicolò Cesa-Bianchi, Tommaso Cesari, Vianney Perchet

ICML 2019 Exploiting Structure of Uncertainty for Efficient Matroid Semi-Bandits Pierre Perrault, Vianney Perchet, Michal Valko

AISTATS 2019 Finding the Bandit in a Graph: Sequential Search-and-Stop Pierre Perrault, Vianney Perchet, Michal Valko

ICML 2019 Learning to Bid in Revenue-Maximizing Auctions Thomas Nedelec, Noureddine El Karoui, Vianney Perchet

AISTATS 2019 Regularized Contextual Bandits Xavier Fontaine, Quentin Berthet, Vianney Perchet

NeurIPS 2019 SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits Etienne Boursier, Vianney Perchet

UAI 2018 Bandits with Side Observations: Bounded vs. Logarithmic Regret Rémy Degenne, Evrard Garcelon, Vianney Perchet

COLT 2018 Conference on Learning Theory, COLT 2018, Stockholm, Sweden, 6-9 July 2018 Sébastien Bubeck, Vianney Perchet, Philippe Rigollet

NeurIPS 2017 Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe Quentin Berthet, Vianney Perchet

AISTATS 2017 Online Learning and Blackwell Approachability with Partial Monitoring: Optimal Convergence Rates Joon Kwon, Vianney Perchet

COLT 2017 Sparse Stochastic Bandits Joon Kwon, Vianney Perchet, Claire Vernade

UAI 2017 Stochastic Bandit Models for Delayed Conversions Claire Vernade, Olivier Cappé, Vianney Perchet

ICML 2016 Anytime Optimal Algorithms in Stochastic Multi-Armed Bandits Rémy Degenne, Vianney Perchet

NeurIPS 2016 Combinatorial Semi-Bandit with Known Covariance Rémy Degenne, Vianney Perchet

JMLR 2016 Gains and Losses Are Fundamentally Different in Regret Minimization: The Sparse Case Joon Kwon, Vianney Perchet

COLT 2016 Highly-Smooth Zero-Th Order Online Optimization Francis R. Bach, Vianney Perchet

COLT 2016 Online Learning and Blackwell Approachability in Quitting Games János Flesch, Rida Laraki, Vianney Perchet

COLT 2016 Online Learning in Repeated Auctions Jonathan Weed, Vianney Perchet, Philippe Rigollet

COLT 2015 Batched Bandit Problems Vianney Perchet, Philippe Rigollet, Sylvain Chassang, Erik Snowberg

COLT 2014 Approachability in Unknown Games: Online Learning Meets Multi-Objective Optimization Shie Mannor, Vianney Perchet, Gilles Stoltz

ICML 2014 Gaussian Process Optimization with Mutual Information Emile Contal, Vianney Perchet, Nicolas Vayatis

JMLR 2014 Set-Valued Approachability and Online Learning with Partial Monitoring Shie Mannor, Vianney Perchet, Gilles Stoltz

COLT 2013 Approachability, Fast and Slow Vianney Perchet, Shie Mannor

COLT 2013 Bounded Regret in Stochastic Multi-Armed Bandits Sébastien Bubeck, Vianney Perchet, Philippe Rigollet

JMLR 2011 Internal Regret with Partial Monitoring: Calibration-Based Optimal Algorithms Vianney Perchet

COLT 2011 Robust Approachability and Regret Minimization in Games with Partial Monitoring Shie Mannor, Vianney Perchet, Gilles Stoltz

ALT 2009 Calibration and Internal No-Regret with Random Signals Vianney Perchet