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On Biased Compression for Distributed Learning
[article]
2024
arXiv
pre-print
In the last few years, various communication compression techniques have emerged as an indispensable tool helping to alleviate the communication bottleneck in distributed learning. However, despite the fact biased compressors often show superior performance in practice when compared to the much more studied and understood unbiased compressors, very little is known about them. In this work we study three classes of biased compression operators, two of which are new, and their performance when
arXiv:2002.12410v4
fatcat:vnkkjpceojb5tkymcwffqkyewa