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Convergence of Variance-Reduced Stochastic Learning under Random Reshuffling. (arXiv:1708.01383v1 [cs.LG])

来源于:arXiv
Several useful variance-reduced stochastic gradient algorithms, such as SVRG, SAGA, Finito, and SAG, have been proposed to minimize empirical risks with linear convergence properties to the exact mini

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