Proposes DCSMD-SW for distributed composite optimization over time-varying networks, deriving high-probability convergence rates under sub-Weibull gradient noise without smoothness assumptions.
Distributed mirror descent method for multi-agent opti- mization with delay
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High-Probability Convergence Theory for Distributed Composite Optimization with Sub-Weibull Noises
Proposes DCSMD-SW for distributed composite optimization over time-varying networks, deriving high-probability convergence rates under sub-Weibull gradient noise without smoothness assumptions.