66 citations · 324 across the 32 of their papers we have counts for
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math.OC2019★ 31 cited
A unified variance-reduced accelerated gradient method for convex optimization
Guanghui Lan, Zhize Li, Yi Zhou
We propose a novel randomized incremental gradient algorithm, namely, VAriance-Reduced Accelerated Gradient (Varag), for finite-sum optimization. Equipped with a unified step-size…
cs.LG2019★ 9 cited
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization
Rong Ge, Zhize Li, Weiyao Wang +1
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…
cs.LG2019
SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points
Zhize Li
We analyze stochastic gradient algorithms for optimizing nonconvex problems. In particular, our goal is to find local minima (second-order stationary points) instead of just findin…