Unified analysis shows decentralized ProxSkip achieves linear speedup in number of nodes under stochastic gradients for non-convex problems.
Variance reduced EXTRA and DIGing and their optimal acceleration for strongly convex decentralized optimiza- tion,
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Achieving Linear Speedup with ProxSkip in Distributed Stochastic Optimization
Unified analysis shows decentralized ProxSkip achieves linear speedup in number of nodes under stochastic gradients for non-convex problems.