Decentralized Stochastic Gradient Tracking for Non-convex Empirical Risk Minimization

6 Sep 2019Jiaqi ZhangKeyou You

This paper studies a decentralized stochastic gradient tracking (DSGT) algorithm for a non-convex empirical risk minimization problem over a peer-to-peer network, which is in sharp contrast to the existing DSGT works only for the convex problem. To handle the variance among decentralized datasets, the mini-batch in each node of the network is designed to be proportional to the size of its local dataset... (read more)

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