Stochastic Gradient-Push for Strongly Convex Functions on Time-Varying Directed Graphs

9 Jun 2014Angelia NedicAlex Olshevsky

We investigate the convergence rate of the recently proposed subgradient-push method for distributed optimization over time-varying directed graphs. The subgradient-push method can be implemented in a distributed way without requiring knowledge of either the number of agents or the graph sequence; each node is only required to know its out-degree at each time... (read more)

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