A unified framework for decentralized stochastic subgradient methods with compressed communication is proposed, proving global convergence for nonsmooth nonconvex objectives via differential inclusions and developing new variants with numerical support.
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Decentralized Stochastic Subgradient-type Methods with Communication Compression for Nonsmooth Nonconvex Optimization
A unified framework for decentralized stochastic subgradient methods with compressed communication is proposed, proving global convergence for nonsmooth nonconvex objectives via differential inclusions and developing new variants with numerical support.