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Andrei Kulunchakov

2 accepted papers

2019

A Generic Acceleration Framework for Stochastic Composite Optimization

NeurIPS 2019poster

In this paper, we introduce various mechanisms to obtain accelerated first-order stochastic optimization algorithms when the objective function is convex or strongly convex. Specifically, we extend the Catalyst approach originally designed for deterministic objectives to the stochastic setting. Give…