The paper develops two variants of a distributed inexact SCA-ADMM algorithm and proves first-order convergence rate guarantees under mild assumptions for non-convex problems with robustness to errors and delays.
Stochastic majorization-minimization algorithms for large- scale optimization,
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Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I
The paper develops two variants of a distributed inexact SCA-ADMM algorithm and proves first-order convergence rate guarantees under mild assumptions for non-convex problems with robustness to errors and delays.