167 citations · 796 across the 44 of their papers we have counts for
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cs.LG2021
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee
Tianhao Wu, Yunchang Yang, Han Zhong +3
Policy optimization methods are one of the most widely used classes of Reinforcement Learning (RL) algorithms. However, theoretical understanding of these methods remains insuffici…
cs.LG2021★ 33 cited
Understanding Domain Randomization for Sim-to-real Transfer
Xiaoyu Chen, Jiachen Hu, Chi Jin +2
Reinforcement learning encounters many challenges when applied directly in the real world. Sim-to-real transfer is widely used to transfer the knowledge learned from simulation to…
cs.LG2021★ 23 cited
FedCM: Federated Learning with Client-level Momentum
Jing Xu, Sen Wang, Liwei Wang +1
Federated Learning is a distributed machine learning approach which enables model training without data sharing. In this paper, we propose a new federated learning algorithm, Feder…