4 citations · 12 across the 10 of their papers we have counts for
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cs.LG2022★ 1 cited
Provably Efficient Fictitious Play Policy Optimization for Zero-Sum Markov Games with Structured Transitions
Shuang Qiu, Xiaohan Wei, Jieping Ye +2
While single-agent policy optimization in a fixed environment has attracted a lot of research attention recently in the reinforcement learning community, much less is known theoret…
cs.LG2021★ 4 cited
On Reward-Free RL with Kernel and Neural Function Approximations: Single-Agent MDP and Markov Game
Shuang Qiu, Jieping Ye, Zhaoran Wang +1
To achieve sample efficiency in reinforcement learning (RL), it necessitates efficiently exploring the underlying environment. Under the offline setting, addressing the exploration…
cs.LG2018
GESF: A Universal Discriminative Mapping Mechanism for Graph Representation Learning
Shupeng Gui, Xiangliang Zhang, Shuang Qiu +3
Graph embedding is a central problem in social network analysis and many other applications, aiming to learn the vector representation for each node. While most existing approaches…