Calibration and Internal No-Regret with Random Signals. - Vianney Perchet (ALT, 2009)

Calibration and Internal no-Regret with Partial Monitoring - Vianney Perchet (CoRR, 2010)

The multi-armed bandit problem with covariates - Vianney Perchet; Philippe Rigollet (CoRR, 2011)

Robust approachability and regret minimization in games with partial monitoring. - Shie Mannor; Vianney Perchet; Gilles Stoltz (COLT, 2011)

Internal Regret with Partial Monitoring: Calibration-Based Optimal Algorithms. - Vianney Perchet (J. Mach. Learn. Res., 2011)

Approachability of Convex Sets in Games with Partial Monitoring. - Vianney Perchet (J. Optim. Theory Appl., 2011)

Bounded regret in stochastic multi-armed bandits. - Sébastien Bubeck; Vianney Perchet; Philippe Rigollet (COLT, 2013)

Approachability, fast and slow. - Vianney Perchet; Shie Mannor (COLT, 2013)

Nash equilibria with partial monitoring; Computation and Lemke-Howson algorithm - Vianney Perchet (CoRR, 2013)

Approachability, Regret and Calibration; implications and equivalences - Vianney Perchet (CoRR, 2013)

On an unified framework for approachability in games with or without signals - Vianney Perchet; Marc Quincampoix (CoRR, 2013)

A Primal Condition for Approachability with Partial Monitoring - Shie Mannor; Vianney Perchet; Gilles Stoltz (CoRR, 2013)

Approachability in unknown games: Online learning meets multi-objective optimization. - Shie Mannor; Vianney Perchet; Gilles Stoltz (COLT, 2014)

Gaussian Process Optimization with Mutual Information. - Emile Contal; Vianney Perchet; Nicolas Vayatis (ICML, 2014)

Set-valued approachability and online learning with partial monitoring. - Shie Mannor; Vianney Perchet; Gilles Stoltz (J. Mach. Learn. Res., 2014)

A note on robust Nash equilibria with uncertainties. - Vianney Perchet (RAIRO Oper. Res., 2014)

Batched Bandit Problems. - Vianney Perchet; Philippe Rigollet; Sylvain Chassang; Erik Snowberg (COLT, 2015)

Exponential Weight Approachability, Applications to Calibration and Regret Minimization. - Vianney Perchet (Dyn. Games Appl., 2015)

On a Unified Framework for Approachability with Full or Partial Monitoring. - Vianney Perchet; Marc Quincampoix (Math. Oper. Res., 2015)

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, 2016)

Anytime optimal algorithms in stochastic multi-armed bandits. - Rémy Degenne; Vianney Perchet (ICML, 2016)

Combinatorial semi-bandit with known covariance. - Rémy Degenne; Vianney Perchet (NIPS, 2016)

Highly-Smooth Zero-th Order Online Optimization Vianney Perchet. - Francis R. Bach; Vianney Perchet (CoRR, 2016)

Gains and Losses are Fundamentally Different in Regret Minimization: The Sparse Case. - Joon Kwon; Vianney Perchet (J. Mach. Learn. Res., 2016)

Quantitative Analysis of Dynamic Fault Trees Based on the Coupling of Structure Functions and Monte Carlo Simulation. - Guillaume Merle; Jean-Marc Roussel; Jean-Jacques Lesage; Vianney Perchet; Nicolas Vayatis (Qual. Reliab. Eng. Int., 2016)

Online Learning and Blackwell Approachability with Partial Monitoring: Optimal Convergence Rates. - Joon Kwon; Vianney Perchet (AISTATS, 2017)

Sparse Stochastic Bandits. - Joon Kwon; Vianney Perchet; Claire Vernade (COLT, 2017)

Fast Rates for Bandit Optimization with Upper-Confidence Frank-Wolfe. - Quentin Berthet; Vianney Perchet (NIPS, 2017)

Stochastic Bandit Models for Delayed Conversions. - Claire Vernade; Olivier Cappé; Vianney Perchet (UAI, 2017)

Bandit Optimization with Upper-Confidence Frank-Wolfe. - Quentin Berthet; Vianney Perchet (CoRR, 2017)

A comparative study of counterfactual estimators. - Thomas Nedelec; Nicolas Le Roux; Vianney Perchet (CoRR, 2017)

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

Explicit shading strategies for repeated truthful auctions. - Marc Abeille; Clément Calauzènes; Noureddine El Karoui; Thomas Nedelec; Vianney Perchet (CoRR, 2018)

Thresholding the virtual value: a simple method to increase welfare and lower reserve prices in online auction systems. - Thomas Nedelec; Marc Abeille; Clément Calauzènes; Noureddine El Karoui; Benjamin Heymann; Vianney Perchet (CoRR, 2018)

A differential game on Wasserstein space. Application to weak approachability with partial monitoring. - Vianney Perchet; Marc Quincampoix (CoRR, 2018)

Approachability of convex sets in generalized quitting games. - János Flesch; Rida Laraki; Vianney Perchet (Games Econ. Behav., 2018)

Bridging the gap between regret minimization and best arm identification, with application to A/B tests. - Rémy Degenne; Thomas Nedelec; Clément Calauzènes; Vianney Perchet (AISTATS, 2019)

Regularized Contextual Bandits. - Xavier Fontaine; Quentin Berthet; Vianney Perchet (AISTATS, 2019)

Finding the bandit in a graph: Sequential search-and-stop. - Pierre Perrault; Vianney Perchet; Michal Valko (AISTATS, 2019)

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

Markov Decision Process for MOOC Users Behavioral Inference. - Firas Jarboui; Célya Gruson-Daniel; Alain Durmus; Vincent Rocchisani; Sophie-Helene Goulet Ebongue; Anneliese Depoux; Wilfried Kirschenmann; Vianney Perchet (EMOOCs, 2019)

Learning to bid in revenue-maximizing auctions. - Thomas Nedelec; Noureddine El Karoui; Vianney Perchet (ICML, 2019)

Exploiting structure of uncertainty for efficient matroid semi-bandits. - Pierre Perrault; Vianney Perchet; Michal Valko (ICML, 2019)

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

Categorized Bandits. - Matthieu Jedor; Vianney Perchet; Jonathan Louëdec (NeurIPS, 2019)

Learning to Bid in Revenue Maximizing Auction. - Thomas Nedelec; Noureddine El Karoui; Vianney Perchet (WWW (Companion Volume), 2019)

Exploiting Structure of Uncertainty for Efficient Combinatorial Semi-Bandits. - Pierre Perrault; Vianney Perchet; Michal Valko (CoRR, 2019)

A Problem-Adaptive Algorithm for Resource Allocation. - Xavier Fontaine; Shie Mannor; Vianney Perchet (CoRR, 2019)

Private Learning and Regularized Optimal Transport. - Etienne Boursier; Vianney Perchet (CoRR, 2019)

Repeated A/B Testing. - Nicolò Cesa-Bianchi; Tommaso Cesari; Yishay Mansour; Vianney Perchet (CoRR, 2019)

Active Linear Regression. - Xavier Fontaine; Pierre Perrault; Vianney Perchet (CoRR, 2019)

Utility/Privacy Trade-off through the lens of Optimal Transport. - Etienne Boursier; Vianney Perchet (AISTATS, 2020)

A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players. - Abbas Mehrabian; Etienne Boursier; Emilie Kaufmann; Vianney Perchet (AISTATS, 2020)

Robust Stackelberg buyers in repeated auctions. - Thomas Nedelec; Clément Calauzènes; Vianney Perchet; Noureddine El Karoui (AISTATS, 2020)

An adaptive stochastic optimization algorithm for resource allocation. - Xavier Fontaine; Shie Mannor; Vianney Perchet (ALT, 2020)

Finding Robust Nash equilibria. - Vianney Perchet (ALT, 2020)

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

Covariance-adapting algorithm for semi-bandits with application to sparse outcomes. - Pierre Perrault; Michal Valko; Vianney Perchet (COLT, 2020)

Trajectory representation learning for Multi-Task NMRDP planning. - Firas Jarboui; Vianney Perchet (ICPR, 2020)

Robustness of Community Detection to Random Geometric Perturbations. - Sandrine Péché; Vianney Perchet (NeurIPS, 2020)

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

Speed of Social Learning from Reviews in Non-Stationary Environments. - Etienne Boursier; Vianney Perchet; Marco Scarsini (CoRR, 2020)

Local Differentially Private Regret Minimization in Reinforcement Learning. - Evrard Garcelon; Vianney Perchet; Ciara Pike-Burke; Matteo Pirotta (CoRR, 2020)

Lifelong Learning in Multi-Armed Bandits. - Matthieu Jedor; Jonathan Louëdec; Vianney Perchet (CoRR, 2020)

Adversarial Learning in Revenue-Maximizing Auctions. - Thomas Nedelec; Jules Baudet; Vianney Perchet; Noureddine El Karoui (AAMAS, 2021)

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

Pure Exploration and Regret Minimization in Matching Bandits. - Flore Sentenac; Jialin Yi; Clément Calauzènes; Vianney Perchet; Milan Vojnovic (ICML, 2021)

Making the most of your day: online learning for optimal allocation of time. - Etienne Boursier; Tristan Garrec; Vianney Perchet; Marco Scarsini (NeurIPS, 2021)

A New Theoretical Framework for Fast and Accurate Online Decision-Making. - Nicolò Cesa-Bianchi; Tommaso Cesari; Yishay Mansour; Vianney Perchet (NeurIPS, 2021)

Local Differential Privacy for Regret Minimization in Reinforcement Learning. - Evrard Garcelon; Vianney Perchet; Ciara Pike-Burke; Matteo Pirotta (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; Odalric-Ambrym Maillard; Vianney Perchet (NeurIPS, 2021)

Stochastic Online Linear Regression: the Forward Algorithm to Replace Ridge. - Reda Ouhamma; Odalric-Ambrym Maillard; Vianney Perchet (NeurIPS, 2021)

Decentralized Learning in Online Queuing Systems. - Flore Sentenac; Etienne Boursier; Vianney Perchet (NeurIPS, 2021)

Be Greedy in Multi-Armed Bandits. - Matthieu Jedor; Jonathan Louëdec; Vianney Perchet (CoRR, 2021)

Homomorphically Encrypted Linear Contextual Bandit. - Evrard Garcelon; Vianney Perchet; Matteo Pirotta (CoRR, 2021)

A Generalised Inverse Reinforcement Learning Framework. - Firas Jarboui; Vianney Perchet (CoRR, 2021)

Quickest change detection with unknown parameters: Constant complexity and near optimality. - Firas Jarboui; Vianney Perchet (CoRR, 2021)

Offline Inverse Reinforcement Learning. - Firas Jarboui; Vianney Perchet (CoRR, 2021)

Unsupervised Neural Hidden Markov Models with a Continuous latent state space. - Firas Jarboui; Vianney Perchet (CoRR, 2021)

Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits. - Reda Ouhamma; Rémy Degenne; Pierre Gaillard; Vianney Perchet (CoRR, 2021)

Encrypted Linear Contextual Bandit. - Evrard Garcelon; Matteo Pirotta; Vianney Perchet (AISTATS, 2022)

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

Privacy Amplification via Shuffling for Linear Contextual Bandits. - Evrard Garcelon; Kamalika Chaudhuri; Vianney Perchet; Matteo Pirotta (ALT, 2022)

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

An Algorithmic Solution to the Blotto Game using Multi-marginal Couplings. - Vianney Perchet; Philippe Rigollet; Thibaut Le Gouic (EC, 2022)

Static Scheduling with Predictions Learned through Efficient Exploration. - Hugo Richard; Flore Sentenac; Corentin Odic; Mathieu Molina; Vianney Perchet (CoRR, 2022)

Learning in Repeated Auctions. - Thomas Nedelec; Clément Calauzènes; Noureddine El Karoui; Vianney Perchet (Found. Trends Mach. Learn., 2022)

Revenue-Maximizing Auctions: A Bidder's Standpoint. - Thomas Nedelec; Clément Calauzènes; Vianney Perchet; Noureddine El Karoui (Oper. Res., 2022)

Stochastic Mirror Descent for Large-Scale Sparse Recovery. - Sasila Ilandarideva; Yannis Bekri; Anatoli B. Juditsky; Vianney Perchet (AISTATS, 2023)

Adapting to game trees in zero-sum imperfect information games. - Côme Fiegel; Pierre Ménard; Tadashi Kozuno; Rémi Munos; Vianney Perchet; Michal Valko (ICML, 2023)

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

Advice Querying under Budget Constraint for Online Algorithms. - Ziyad Benomar; Vianney Perchet (NeurIPS, 2023)

Trading-off price for data quality to achieve fair online allocation. - Mathieu Molina; Nicolas Gast; Patrick Loiseau; Vianney Perchet (NeurIPS, 2023)

Constant or logarithmic regret in asynchronous multiplayer bandits. - Hugo Richard; Etienne Boursier; Vianney Perchet (CoRR, 2023)

Online Matching in Geometric Random Graphs. - Flore Sentenac; Nathan Noiry; Matthieu Lerasle; Laurent Ménard; Vianney Perchet (CoRR, 2023)

Multi-armed bandits with guaranteed revenue per arm. - Dorian Baudry; Nadav Merlis; Mathieu Benjamin Molina; Hugo Richard; Vianney Perchet (AISTATS, 2024)

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

Mode Estimation with Partial Feedback. - Charles Arnal; Vivien Cabannes; Vianney Perchet (COLT, 2024)

Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithms. - Ahmed Ben Yahmed; Clément Calauzènes; Vianney Perchet (ICASSP, 2024)

Non-clairvoyant Scheduling with Partial Predictions. - Ziyad Benomar; Vianney Perchet (ICML, 2024)

Active Ranking and Matchmaking, with Perfect Matchings. - Hafedh El Ferchichi; Matthieu Lerasle; Vianney Perchet (ICML, 2024)

Optimizing the coalition gain in Online Auctions with Greedy Structured Bandits. - Dorian Baudry; Hugo Richard; Maria Cherifa; Vianney Perchet; Clément Calauzènes (NeurIPS, 2024)

Lookback Prophet Inequalities. - Ziyad Benomar; Dorian Baudry; Vianney Perchet (NeurIPS, 2024)

Addressing Bias in Online Selection with Limited Budget of Comparisons. - Ziyad Benomar; Evgenii Chzhen; Nicolas Schreuder; Vianney Perchet (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)

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

The Value of Reward Lookahead in Reinforcement Learning. - Nadav Merlis; Dorian Baudry; 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)

Improved Algorithms for Contextual Dynamic Pricing. - Matilde Tullii; Solenne Gaucher; Nadav Merlis; Vianney Perchet (NeurIPS, 2024)

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

Calibrated Forecasting and Persuasion. - Atulya Jain; Vianney Perchet (EC, 2024)

Open Research Challenges for Private Advertising Systems Under Local Differential Privacy. - Matilde Tullii; Solenne Gaucher; Hugo Richard; Eustache Diemert; Vianney Perchet; Alain Rakotomamonjy; Clément Calauzènes; Maxime Vono (WISE (5), 2024)

The Price of Fairness in Bipartite Matching. - Rémi Castera; Felipe Garrido-Lucero; Mathieu Molina; Simon Mauras; Patrick Loiseau; Vianney Perchet (CoRR, 2024)

Dynamic online matching with budget refills. - Maria Cherifa; Clément Calauzènes; Vianney Perchet (CoRR, 2024)

Prophet Inequalities: Competing with the Top ℓ Items is Easy. - Mathieu Molina; Nicolas Gast; Patrick Loiseau; Vianney Perchet (CoRR, 2024)

Stable Matching with Ties: Approximation Ratios and Learning. - Shiyun Lin; Simon Mauras; Nadav Merlis; Vianney Perchet (CoRR, 2024)

An Algorithmic Solution to the Blotto Game Using Multimarginal Couplings. - Vianney Perchet; Philippe Rigollet; Thibaut Le Gouic (Oper. Res., 2024)

A Survey on Multi-player Bandits. - Etienne Boursier; Vianney Perchet (J. Mach. Learn. Res., 2024)

Utility/privacy trade-off as regularized optimal transport. - Etienne Boursier; Vianney Perchet (Math. Program., 2024)

On Tradeoffs in Learning-Augmented Algorithms. - Ziyad Benomar; Vianney Perchet (AISTATS, 2025)

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

Prophet Inequalities: Competing with the Top ℓ Items is Easy. - Mathieu Molina; Nicolas Gast; Patrick Loiseau; Vianney Perchet (SODA, 2025)

Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search. - Ziyad Benomar; Lorenzo Croissant; Vianney Perchet; Spyros Angelopoulos 001 (CoRR, 2025)

Online matching on stochastic block model. - Maria Cherifa; Clément Calauzènes; Vianney Perchet (CoRR, 2025)