49 citations · 79 across the 9 of their papers we have counts for
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cs.LG2020
Improved Worst-Case Regret Bounds for Randomized Least-Squares Value Iteration
Priyank Agrawal, Jinglin Chen, Nan Jiang
This paper studies regret minimization with randomized value functions in reinforcement learning. In tabular finite-horizon Markov Decision Processes, we introduce a clipping varia…
cs.LG2020★ 13 cited
Nonstationary Reinforcement Learning with Linear Function Approximation
Huozhi Zhou, Jinglin Chen, Lav R. Varshney +1
We consider reinforcement learning (RL) in episodic Markov decision processes (MDPs) with linear function approximation under drifting environment. Specifically, both the reward an…