212 citations · 575 across the 20 of their papers we have counts for
4 papers · 1 filter
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation
Jiafan He, Dongruo Zhou, Quanquan Gu
Reinforcement learning (RL) with linear function approximation has received increasing attention recently. However, existing work has focused on obtaining -type regret bo…
Provable Multi-Objective Reinforcement Learning with Generative Models
Dongruo Zhou, Jiahao Chen, Quanquan Gu
Multi-objective reinforcement learning (MORL) is an extension of ordinary, single-objective reinforcement learning (RL) that is applicable to many real-world tasks where multiple o…
Neural Thompson Sampling
Weitong Zhang, Dongruo Zhou, Lihong Li +1
Thompson Sampling (TS) is one of the most effective algorithms for solving contextual multi-armed bandit problems. In this paper, we propose a new algorithm, called Neural Thompson…
Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou, Jiafan He, Quanquan Gu
Modern tasks in reinforcement learning have large state and action spaces. To deal with them efficiently, one often uses predefined feature mapping to represent states and actions…