Pierre Ménard

research

∙ 09/01/2023

Local and adaptive mirror descents in extensive-form games

We study how to learn ϵ-optimal strategies in zero-sum imperfect informa...

0 Côme Fiegel, et al. ∙

research

∙ 05/22/2023

Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice

Mirror descent value iteration (MDVI), an abstraction of Kullback-Leible...

0 Toshinori Kitamura, et al. ∙

research

∙ 04/06/2023

Sharp Deviations Bounds for Dirichlet Weighted Sums with Application to analysis of Bayesian algorithms

In this work, we derive sharp non-asymptotic deviation bounds for weight...

0 Denis Belomestny, et al. ∙

research

∙ 03/26/2023

Learning Generative Models with Goal-conditioned Reinforcement Learning

We present a novel, alternative framework for learning generative models...

0 Mariana Vargas Vieyra, et al. ∙

research

∙ 03/14/2023

Fast Rates for Maximum Entropy Exploration

We consider the reinforcement learning (RL) setting, in which the agent ...

0 Daniil Tiapkin, et al. ∙

research

∙ 12/23/2022

Adapting to game trees in zero-sum imperfect information games

Imperfect information games (IIG) are games in which each player only pa...

0 Côme Fiegel, et al. ∙

research

∙ 09/28/2022

Optimistic Posterior Sampling for Reinforcement Learning with Few Samples and Tight Guarantees

We consider reinforcement learning in an environment modeled by an episo...

0 Daniil Tiapkin, et al. ∙

research

∙ 05/27/2022

KL-Entropy-Regularized RL with a Generative Model is Minimax Optimal

In this work, we consider and analyze the sample complexity of model-fre...

6 Tadashi Kozuno, et al. ∙

research

∙ 05/16/2022

From Dirichlet to Rubin: Optimistic Exploration in RL without Bonuses

We propose the Bayes-UCBVI algorithm for reinforcement learning in tabul...

0 Daniil Tiapkin, et al. ∙

research

∙ 12/02/2021

Indexed Minimum Empirical Divergence for Unimodal Bandits

We consider a multi-armed bandit problem specified by a set of one-dimen...

0 Hassan Saber, et al. ∙

research

∙ 11/23/2021

Adaptive Multi-Goal Exploration

We introduce a generic strategy for provably efficient multi-goal explor...

0 Jean Tarbouriech, et al. ∙

research

∙ 06/18/2021

Problem Dependent View on Structured Thresholding Bandit Problems

We investigate the problem dependent regime in the stochastic Thresholdi...

0 James Cheshire, et al. ∙

research

∙ 06/11/2021

Model-Free Learning for Two-Player Zero-Sum Partially Observable Markov Games with Perfect Recall

We study the problem of learning a Nash equilibrium (NE) in an imperfect...

0 Tadashi Kozuno, et al. ∙

research

∙ 03/23/2021

Bandits with many optimal arms

We consider a stochastic bandit problem with a possibly infinite number ...

0 Rianne de Heide, et al. ∙

research

∙ 03/01/2021

UCB Momentum Q-learning: Correcting the bias without forgetting

We propose UCBMQ, Upper Confidence Bound Momentum Q-learning, a new algo...

0 Pierre Ménard, et al. ∙

research

∙ 10/07/2020

Episodic Reinforcement Learning in Finite MDPs: Minimax Lower Bounds Revisited

In this paper, we propose new problem-independent lower bounds on the sa...

0 Omar Darwiche Domingues, et al. ∙

research

∙ 07/27/2020

Fast active learning for pure exploration in reinforcement learning

Realistic environments often provide agents with very limited feedback. ...

10 Pierre Ménard, et al. ∙

research

∙ 07/09/2020

A Kernel-Based Approach to Non-Stationary Reinforcement Learning in Metric Spaces

In this work, we propose KeRNS: an algorithm for episodic reinforcement ...

51 Omar Darwiche Domingues, et al. ∙

research

∙ 07/07/2020

Optimal Strategies for Graph-Structured Bandits

We study a structured variant of the multi-armed bandit problem specifie...

0 Hassan Saber, et al. ∙

research

∙ 07/02/2020

Gamification of Pure Exploration for Linear Bandits

We investigate an active pure-exploration setting, that includes best-ar...

0 Rémy Degenne, et al. ∙

research

∙ 06/30/2020

Forced-exploration free Strategies for Unimodal Bandits

We consider a multi-armed bandit problem specified by a set of Gaussian ...

0 Hassan Saber, et al. ∙

research

∙ 06/17/2020

The Influence of Shape Constraints on the Thresholding Bandit Problem

We investigate the stochastic Thresholding Bandit problem (TBP) under se...

0 James Cheshire, et al. ∙

research

∙ 06/11/2020

Adaptive Reward-Free Exploration

Reward-free exploration is a reinforcement learning setting recently stu...

3 Emilie Kaufmann, et al. ∙

research

∙ 06/10/2020

Planning in Markov Decision Processes with Gap-Dependent Sample Complexity

We propose MDP-GapE, a new trajectory-based Monte-Carlo Tree Search algo...

10 Anders Jonsson, et al. ∙

research

∙ 04/12/2020

Regret Bounds for Kernel-Based Reinforcement Learning

We consider the exploration-exploitation dilemma in finite-horizon reinf...

0 Omar Darwiche Domingues, et al. ∙

research

∙ 10/24/2019

Fixed-Confidence Guarantees for Bayesian Best-Arm Identification

We investigate and provide new insights on the sampling rule called Top-...

0 Xuedong Shang, et al. ∙

research

∙ 06/25/2019

Non-Asymptotic Pure Exploration by Solving Games

Pure exploration (aka active testing) is the fundamental task of sequent...

0 Rémy Degenne, et al. ∙

research

∙ 05/20/2019

Gradient Ascent for Active Exploration in Bandit Problems

We present a new algorithm based on an gradient ascent for a general Act...

0 Pierre Ménard, et al. ∙

research

∙ 05/14/2018

KL-UCB-switch: optimal regret bounds for stochastic bandits from both a distribution-dependent and a distribution-free viewpoints

In the context of K-armed stochastic bandits with distribution only assu...

0 Aurélien Garivier, et al. ∙

research

∙ 11/13/2017

Thresholding Bandit for Dose-ranging: The Impact of Monotonicity

We analyze the sample complexity of the thresholding bandit problem, wit...

0 Aurélien Garivier, et al. ∙

research

∙ 02/23/2017

A minimax and asymptotically optimal algorithm for stochastic bandits

We propose the kl-UCB ++ algorithm for regret minimization in stochastic...

0 Pierre Ménard, et al. ∙

Pierre Ménard

Featured Co-authors