15 citations · 33 across the 12 of their papers we have counts for
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cs.LG2021★ 1 cited
Faster Rates for Compressed Federated Learning with Client-Variance Reduction
Haoyu Zhao, Konstantin Burlachenko, Zhize Li +1
Due to the communication bottleneck in distributed and federated learning applications, algorithms using communication compression have attracted significant attention and are wide…
cs.LG2021★ 15 cited
MARINA: Faster Non-Convex Distributed Learning with Compression
Eduard Gorbunov, Konstantin Burlachenko, Zhize Li +1
We develop and analyze MARINA: a new communication efficient method for non-convex distributed learning over heterogeneous datasets. MARINA employs a novel communication compressio…