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cs.LG2022★ 1 cited
Adaptive Compression for Communication-Efficient Distributed Training
Maksim Makarenko, Elnur Gasanov, Rustem Islamov +2
We propose Adaptive Compressed Gradient Descent (AdaCGD) - a novel optimization algorithm for communication-efficient training of supervised machine learning models with adaptive c…
cs.LG2021★ 2 cited
Basis Matters: Better Communication-Efficient Second Order Methods for Federated Learning
Xun Qian, Rustem Islamov, Mher Safaryan +1
Recent advances in distributed optimization have shown that Newton-type methods with proper communication compression mechanisms can guarantee fast local rates and low communicatio…