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Creators/Authors contains: "Wang, Weiyao"

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  1. ; ; ( , 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE))
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  2. ; ; ; ( , 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE))
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  3. ; ; ; ( , The 32’nd Annual Conference on Learning Theory (COLT 2019))
    Variance reduction techniques like SVRG provide simple and fast algorithms for optimizing a convex finite-sum objective. For nonconvex objectives, these techniques can also find a first-order stationary point (with small gradient). However, in nonconvex optimization it is often crucial to find a second-order stationary point (with small gradient and almost PSD hessian). In this paper, we show that Stabilized SVRG (a simple variant of SVRG) can find an \eps-second-order stationary point using only O(n^{2/3}/\eps^2+n/\eps^{1.5}) stochastic gradients. To our best knowledge, this is the first second-order guarantee for a simple variant of SVRG. The running time almost matches the known guarantees for finding \eps-first-order stationary points. 
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  4. ; ; ; ; ; ; ; ; ; ( , ACS Central Science)