Vianney Perchet

Feature-Based Online Bilateral Trade ICLR 2025 On Tradeoffs in Learning-Augmented Algorithms AISTATS 2025 Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search ICML 2025 The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback ICML 2025 Active Ranking and Matchmaking, with Perfect Matchings ICML 2024 Addressing Bias in Online Selection with Limited Budget of Comparisons NeurIPS 2024 A Survey on Multi-player Bandits JMLR 2024 Constant or Logarithmic Regret in Asynchronous Multiplayer Bandits with Limited Communication AISTATS 2024 DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation NeurIPS 2024 Improved Algorithms for Contextual Dynamic Pricing NeurIPS 2024 Improved learning rates in multi-unit uniform price auctions NeurIPS 2024 Local and Adaptive Mirror Descents in Extensive-Form Games NeurIPS 2024 Lookback Prophet Inequalities NeurIPS 2024 Mode Estimation with Partial Feedback COLT 2024 Multi-armed bandits with guaranteed revenue per arm AISTATS 2024 Non-clairvoyant Scheduling with Partial Predictions ICML 2024 Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits NeurIPS 2024 Strategic Multi-Armed Bandit Problems Under Debt-Free Reporting NeurIPS 2024 The Value of Reward Lookahead in Reinforcement Learning NeurIPS 2024 Adapting to game trees in zero-sum imperfect information games ICML 2023 Advice Querying under Budget Constraint for Online Algorithms NeurIPS 2023 On Preemption and Learning in Stochastic Scheduling ICML 2023 Stochastic Mirror Descent for Large-Scale Sparse Recovery AISTATS 2023 Trading-off price for data quality to achieve fair online allocation NeurIPS 2023 Active Labeling: Streaming Stochastic Gradients NeurIPS 2022 Encrypted Linear Contextual Bandit AISTATS 2022 Privacy Amplification via Shuffling for Linear Contextual Bandits ALT 2022 Social Learning in Non-Stationary Environments ALT 2022 Decentralized Learning in Online Queuing Systems NeurIPS 2021 Local Differential Privacy for Regret Minimization in Reinforcement Learning NeurIPS 2021 Making the most of your day: online learning for optimal allocation of time NeurIPS 2021 Online A-Optimal Design and Active Linear Regression ICML 2021 Online Matching in Sparse Random Graphs: Non-Asymptotic Performances of Greedy Algorithm NeurIPS 2021 Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits NeurIPS 2021 Pure Exploration and Regret Minimization in Matching Bandits ICML 2021 ROI Maximization in Stochastic Online Decision-Making NeurIPS 2021 Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge NeurIPS 2021 An adaptive stochastic optimization algorithm for resource allocation ALT 2020 A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players AISTATS 2020 Covariance-adapting algorithm for semi-bandits with application to sparse outcomes COLT 2020 Finding Robust Nash equilibria ALT 2020 Robustness of Community Detection to Random Geometric Perturbations NeurIPS 2020 Robust Stackelberg buyers in repeated auctions AISTATS 2020 Selfish Robustness and Equilibria in Multi-Player Bandits COLT 2020 Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits NeurIPS 2020 Utility/Privacy Trade-off through the lens of Optimal Transport AISTATS 2020 Bridging the gap between regret minimization and best arm identification, with application to A/B tests AISTATS 2019 Categorized Bandits NeurIPS 2019 Dynamic Pricing with Finitely Many Unknown Valuations ALT 2019 Exploiting structure of uncertainty for efficient matroid semi-bandits ICML 2019 Finding the bandit in a graph: Sequential search-and-stop AISTATS 2019 Learning to bid in revenue-maximizing auctions ICML 2019 Regularized Contextual Bandits AISTATS 2019 SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits NeurIPS 2019 Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe NeurIPS 2017 Online Learning and Blackwell Approachability with Partial Monitoring: Optimal Convergence Rates AISTATS 2017 Sparse Stochastic Bandits COLT 2017 Anytime optimal algorithms in stochastic multi-armed bandits ICML 2016 Combinatorial semi-bandit with known covariance NeurIPS 2016 Gains and Losses are Fundamentally Different in Regret Minimization: The Sparse Case JMLR 2016 Highly-Smooth Zero-th Order Online Optimization COLT 2016 Online Learning and Blackwell Approachability in Quitting Games COLT 2016 Online learning in repeated auctions COLT 2016 Batched Bandit Problems COLT 2015 Approachability in unknown games: Online learning meets multi-objective optimization COLT 2014 Gaussian Process Optimization with Mutual Information ICML 2014 Set-Valued Approachability and Online Learning with Partial Monitoring JMLR 2014 Approachability, fast and slow COLT 2013 Bounded regret in stochastic multi-armed bandits COLT 2013 Internal Regret with Partial Monitoring: Calibration-Based Optimal Algorithms JMLR 2011 Robust approachability and regret minimization in games with partial monitoring COLT 2011