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...
share
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...
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...
research
∙
03/26/2023
Learning Generative Models with Goal-conditioned Reinforcement Learning
We present a novel, alternative framework for learning generative models...
research
∙
03/14/2023
Fast Rates for Maximum Entropy Exploration
We consider the reinforcement learning (RL) setting, in which the agent ...
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...
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...
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...
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...
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...
research
∙
11/23/2021
Adaptive Multi-Goal Exploration
We introduce a generic strategy for provably efficient multi-goal explor...
research
∙
06/18/2021
Problem Dependent View on Structured Thresholding Bandit Problems
We investigate the problem dependent regime in the stochastic Thresholdi...
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...
research
∙
03/23/2021
Bandits with many optimal arms
We consider a stochastic bandit problem with a possibly infinite number ...
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...
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...
research
∙
07/27/2020
Fast active learning for pure exploration in reinforcement learning
Realistic environments often provide agents with very limited feedback. ...
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 ...
research
∙
07/07/2020
Optimal Strategies for Graph-Structured Bandits
We study a structured variant of the multi-armed bandit problem specifie...
research
∙
07/02/2020
Gamification of Pure Exploration for Linear Bandits
We investigate an active pure-exploration setting, that includes best-ar...
research
∙
06/30/2020
Forced-exploration free Strategies for Unimodal Bandits
We consider a multi-armed bandit problem specified by a set of Gaussian ...
research
∙
06/17/2020
The Influence of Shape Constraints on the Thresholding Bandit Problem
We investigate the stochastic Thresholding Bandit problem (TBP) under se...
research
∙
06/11/2020
Adaptive Reward-Free Exploration
Reward-free exploration is a reinforcement learning setting recently stu...
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...
research
∙
04/12/2020
Regret Bounds for Kernel-Based Reinforcement Learning
We consider the exploration-exploitation dilemma in finite-horizon reinf...
research
∙
10/24/2019
Fixed-Confidence Guarantees for Bayesian Best-Arm Identification
We investigate and provide new insights on the sampling rule called Top-...
research
∙
06/25/2019
Non-Asymptotic Pure Exploration by Solving Games
Pure exploration (aka active testing) is the fundamental task of sequent...
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...
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...
research
∙
11/13/2017
Thresholding Bandit for Dose-ranging: The Impact of Monotonicity
We analyze the sample complexity of the thresholding bandit problem, wit...
research
∙
02/23/2017
