Universal Method for Stochastic Composite Optimization Problems |
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| Authors: | A. V. Gasnikov Yu. E. Nesterov |
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| Affiliation: | 1.Institute for Information Transmission Problems,Russian Academy of Sciences,Moscow,Russia;2.Moscow Institute of Physics and Technology,Dolgoprudnyi, Moscow oblast,Russia;3.National Research University Higher School of Economics,Moscow,Russia;4.Louvain-la-Neuve,Belgium |
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| Abstract: | A fast gradient method requiring only one projection is proposed for smooth convex optimization problems. The method has a visual geometric interpretation, so it is called the method of similar triangles (MST). Composite, adaptive, and universal versions of MST are suggested. Based on MST, a universal method is proposed for the first time for strongly convex problems (this method is continuous with respect to the strong convexity parameter of the smooth part of the functional). It is shown how the universal version of MST can be applied to stochastic optimization problems. |
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