10 citations · 11 across the 11 of their papers we have counts for
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cs.LG2023
Communication Efficient and Privacy-Preserving Federated Learning Based on Evolution Strategies
Guangchen Lan
Federated learning (FL) is an emerging paradigm for training deep neural networks (DNNs) in distributed manners. Current FL approaches all suffer from high communication overhead a…
cs.LG2023★ 10 cited
Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates
Guangchen Lan, Han Wang, James Anderson +2
Federated reinforcement learning (FedRL) enables agents to collaboratively train a global policy without sharing their individual data. However, high communication overhead remains…