62 citations · 146 across the 11 of their papers we have counts for
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cs.LG2022★ 3 cited
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits
Jiafan He, Tianhao Wang, Yifei Min +1
We study federated contextual linear bandits, where agents cooperate with each other to solve a global contextual linear bandit problem with the help of a central server. We co…
cs.LG2022
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
Miao Lu, Yifei Min, Zhaoran Wang +1
We study offline reinforcement learning (RL) in partially observable Markov decision processes. In particular, we aim to learn an optimal policy from a dataset collected by a behav…
cs.LG2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets
Yifei Min, Tianhao Wang, Ruitu Xu +3
We study a Markov matching market involving a planner and a set of strategic agents on the two sides of the market. At each step, the agents are presented with a dynamical context,…