462 citations · 2.5k across the 127 of their papers we have counts for
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Third-order Smoothness Helps: Even Faster Stochastic Optimization Algorithms for Finding Local Minima
Yaodong Yu, Pan Xu, Quanquan Gu
We propose stochastic optimization algorithms that can find local minima faster than existing algorithms for nonconvex optimization problems, by exploiting the third-order smoothne…
Saving Gradient and Negative Curvature Computations: Finding Local Minima More Efficiently
Yaodong Yu, Difan Zou, Quanquan Gu
We propose a family of nonconvex optimization algorithms that are able to save gradient and negative curvature computations to a large extent, and are guaranteed to find an approxi…
Global Convergence of Langevin Dynamics Based Algorithms for Nonconvex Optimization
Pan Xu, Jinghui Chen, Difan Zou +1
We present a unified framework to analyze the global convergence of Langevin dynamics based algorithms for nonconvex finite-sum optimization with component functions. At the co…
Robust Wirtinger Flow for Phase Retrieval with Arbitrary Corruption
Jinghui Chen, Lingxiao Wang, Xiao Zhang +1
We consider the robust phase retrieval problem of recovering the unknown signal from the magnitude-only measurements, where the measurements can be contaminated by both sparse arbi…
Speeding Up Latent Variable Gaussian Graphical Model Estimation via Nonconvex Optimizations
Pan Xu, Jian Ma, Quanquan Gu
We study the estimation of the latent variable Gaussian graphical model (LVGGM), where the precision matrix is the superposition of a sparse matrix and a low-rank matrix. In order…
A Unified Framework for Low-Rank plus Sparse Matrix Recovery
Xiao Zhang, Lingxiao Wang, Quanquan Gu
We propose a unified framework to solve general low-rank plus sparse matrix recovery problems based on matrix factorization, which covers a broad family of objective functions sati…