66 citations · 324 across the 32 of their papers we have counts for
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math.OC2020★ 24 cited
A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization
Zhize Li, Peter Richtárik
In this paper, we study the performance of a large family of SGD variants in the smooth nonconvex regime. To this end, we propose a generic and flexible assumption capable of accur…
math.OC2020★ 66 cited
Acceleration for Compressed Gradient Descent in Distributed and Federated Optimization
Zhize Li, Dmitry Kovalev, Xun Qian +1
Due to the high communication cost in distributed and federated learning problems, methods relying on compression of communicated messages are becoming increasingly popular. While…