Pierre Menard
29 papers · 2017–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π£ Hot Topic Early Bird π§ Keyword Pioneer π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (10) π Conference Polyglot (7)
π§
Keyword Pioneer
π£
Hot Topic Early Bird
π
Academic Marathon
(8)
π€
Dynamic Duo
(22)
π¬
Deep Specialist
(12)
π
Keyword Champion
(2)
π
Conference Pioneer
β‘
Prolific Year
(5)
ποΈ
Keyword Collector
(107)
π
Century Club
(29)
π₯
Unstoppable
(7)
Conferences
ICML (10)
NIPS (9)
AISTATS (4)
ALT (3)
COLT (1)
ICLR (1)
JMLR (1)
Top co-authors
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