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MALCOM-PSGD: Inexact Proximal Stochastic Gradient Descent for Communication-Efficient Decentralized Machine Learning
Recent research indicates that frequent model communication stands as a major bottleneck to the efficiency of decentralized machine learning (ML), particularly for large-scale and over-parameterized neural networks (NNs).
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