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We firstly propose the new stochastic gradient estimate of unbiasedness andminimized variance in this paper. Secondly, we propose the two algorithms:Algorithml and Algorithm2 which apply the new stochastic gradient estimate tomodern stochastic conjugate gradient algorithms SCGA 7and CGVR 8. Then we provethat the proposed algorithms can obtain linearconvergence rate underassumptions of strong convexity and smoothness. Finally, numerical experimentsshow that the new stochastic gradient estimatecan reduce variance of stochasticgradient effectively. And our algorithms compared SCGA and CGVR can convergentfaster in numerical experimentson ridge regression model.

The Mini-batch Stochastic Conjugate Algorithms with the unbiasedness and Minimized Variance Reduction