DSGT provably converges to stationary points for non-convex empirical risk minimization at O(1/sqrt(K)) rates, with network topology affecting only constant factors under stated assumptions.
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Decentralized Stochastic Gradient Tracking for Non-convex Empirical Risk Minimization
DSGT provably converges to stationary points for non-convex empirical risk minimization at O(1/sqrt(K)) rates, with network topology affecting only constant factors under stated assumptions.