2 papers
cs.LG2025
Settling the Sample Complexity of Online Reinforcement Learning
Zihan Zhang, Yuxin Chen, Jason D. Lee +1
A central issue lying at the heart of online reinforcement learning (RL) is data efficiency. While a number of recent works achieved asymptotically minimal regret in online RL, the…
cs.GT2024
Offline congestion games: How feedback type affects data coverage requirement
Haozhe Jiang, Qiwen Cui, Zhihan Xiong +2
This paper investigates when one can efficiently recover an approximate Nash Equilibrium (NE) in offline congestion games. The existing dataset coverage assumption in offline gener…