Tight Complexity Bounds for Optimizing Composite Objectives

NeurIPS 2016 Blake E. WoodworthNati Srebro

We provide tight upper and lower bounds on the complexity of minimizing the average of m convex functions using gradient and prox oracles of the component functions. We show a significant gap between the complexity of deterministic vs randomized optimization... (read more)

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