35 citations · 88 across the 18 of their papers we have counts for
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math.OC2020
Towards accelerated rates for distributed optimization over time-varying networks
Alexander Rogozin, Vladislav Lukoshkin, Alexander Gasnikov +2
We study the problem of decentralized optimization over time-varying networks with strongly convex smooth cost functions. In our approach, nodes run a multi-step gossip procedure a…
cs.LG2020★ 9 cited
Uncertainty Principle for Communication Compression in Distributed and Federated Learning and the Search for an Optimal Compressor
Mher Safaryan, Egor Shulgin, Peter Richtárik
In order to mitigate the high communication cost in distributed and federated learning, various vector compression schemes, such as quantization, sparsification and dithering, have…