A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates

ICML 2017 Tianbao YangQihang LinLijun Zhang

This paper focuses on convex constrained optimization problems, where the solution is subject to a convex inequality constraint. In particular, we aim at challenging problems for which both projection into the constrained domain and a linear optimization under the inequality constraint are time-consuming, which render both projected gradient methods and conditional gradient methods (a.k.a... (read more)

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