Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations

Jialei Wang; Tong Zhang

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arXiv · 1706.07001

Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations

Jialei Wang·Tong Zhang

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Abstract

We present novel minibatch stochastic optimization methods for empirical risk minimization problems, the methods efficiently leverage variance reduced first-order and sub-sampled higher-order information to accelerate the convergence speed. For quadratic objectives, we prove improved iteration complexity over state-of-the-art under reasonable assumptions. We also provide empirical evidence of the advantages of our method compared to existing approaches in the literature.

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BibTeX RIS

Jialei Wang, Tong Zhang. 2017-06-21. Improved Optimization of Finite Sums with Minibatch Stochastic Variance Reduced Proximal Iterations. https://arxiv.org/abs/1706.07001

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