1 citations · 1 across the 14 of their papers we have counts for
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Gap-Dependent Bounds for Q-Learning using Reference-Advantage Decomposition
Zhong Zheng, Haochen Zhang, Lingzhou Xue
We study the gap-dependent bounds of two important algorithms for on-policy Q-learning for finite-horizon episodic tabular Markov Decision Processes (MDPs): UCB-Advantage (Zhang et…
Smoothed Robust Phase Retrieval
Zhong Zheng, Lingzhou Xue
The phase retrieval problem in the presence of noise aims to recover the signal vector of interest from a set of quadratic measurements with infrequent but arbitrary corruptions, a…
Adaptive Algorithms for Robust Phase Retrieval
Zhong Zheng, Necdet Serhat Aybat, Shiqian Ma +1
This paper considers robust phase retrieval, which can be cast as a nonsmooth and nonconvex optimization problem. We propose two first-order algorithms with adaptive step sizes: th…
Federated Q-Learning with Reference-Advantage Decomposition: Almost Optimal Regret and Logarithmic Communication Cost
Zhong Zheng, Haochen Zhang, Lingzhou Xue
In this paper, we consider model-free federated reinforcement learning for tabular episodic Markov decision processes. Under the coordination of a central server, multiple agents c…