← Authors

Pierre Menard

29 papers · 2017–2025 · 7 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (7) 🌈 Renaissance Researcher (5) 🐝 Cross-Pollinator (11) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (8) 🀝 Dynamic Duo (22) πŸ”¬ Deep Specialist (12) πŸ† Keyword Champion (2) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ—ƒοΈ Keyword Collector (107) πŸ’Ž Century Club (29) πŸ”₯ Unstoppable (7)

Conferences

ICML (10) NIPS (9) AISTATS (4) ALT (3) COLT (1) ICLR (1) JMLR (1)

Top co-authors

Michal Valko (22) Omar Darwiche Domingues (9) RΓ©mi Munos (8) Emilie Kaufmann (7) Tadashi Kozuno (5) Eric Moulines (5) Alexey Naumov (5) Denis Belomestny (5) Daniil Tiapkin (5) Daniele Calandriello (4)

Keywords

regret bound (10) sample complexity (8) multi-armed bandit (8) markov decision process (7) upper confidence bound (5) reinforcement learning (4) game theory (3) pure exploration (3) online learning (3) stochastic optimization (3) best-arm identification (3) regret minimization (3) posterior sampling (2) stochastic bandit (2) active learning (2) zero-sum game (2) arm selection (2) bayesian inference (2) mirror descent (2) online mirror descent (2)

Papers

The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback ICML 2025
Demonstration-Regularized RL ICLR 2024
Local and Adaptive Mirror Descents in Extensive-Form Games NIPS 2024
Adapting to game trees in zero-sum imperfect information games ICML 2023
Model-free Posterior Sampling via Learning Rate Randomization NIPS 2023
Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice ICML 2023
Fast Rates for Maximum Entropy Exploration ICML 2023
From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses ICML 2022
KL-UCB-Switch: Optimal Regret Bounds for Stochastic Bandits from Both a Distribution-Dependent and a Distribution-Free Viewpoints JMLR 2022
Adaptive Multi-Goal Exploration AISTATS 2022
Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees NIPS 2022
Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited ALT 2021
Indexed Minimum Empirical Divergence for Unimodal Bandits NIPS 2021
Learning in two-player zero-sum partially observable Markov games with perfect recall NIPS 2021
Bandits with many optimal arms NIPS 2021
A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces AISTATS 2021
Adaptive Reward-Free Exploration ALT 2021
Problem Dependent View on Structured Thresholding Bandit Problems ICML 2021
Kernel-Based Reinforcement Learning: A Finite-Time Analysis ICML 2021
Fast active learning for pure exploration in reinforcement learning ICML 2021
UCB Momentum Q-learning: Correcting the bias without forgetting ICML 2021
Fixed-confidence guarantees for Bayesian best-arm identification AISTATS 2020
Gamification of Pure Exploration for Linear Bandits ICML 2020
A single algorithm for both restless and rested rotting bandits AISTATS 2020
Planning in Markov Decision Processes with Gap-Dependent Sample Complexity NIPS 2020
The Influence of Shape Constraints on the Thresholding Bandit Problem COLT 2020
Non-Asymptotic Pure Exploration by Solving Games NIPS 2019
Planning in entropy-regularized Markov decision processes and games NIPS 2019
A minimax and asymptotically optimal algorithm for stochastic bandits ALT 2017