407 citations · 420 across the 15 of their papers we have counts for
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cs.LG2022★ 4 cited
Robustness to Unbounded Smoothness of Generalized SignSGD
Michael Crawshaw, Mingrui Liu, Francesco Orabona +2
Traditional analyses in non-convex optimization typically rely on the smoothness assumption, namely requiring the gradients to be Lipschitz. However, recent evidence shows that thi…
cs.LG2022★ 3 cited
Fast Composite Optimization and Statistical Recovery in Federated Learning
Yajie Bao, Michael Crawshaw, Shan Luo +1
As a prevalent distributed learning paradigm, Federated Learning (FL) trains a global model on a massive amount of devices with infrequent communication. This paper investigates a…