56 citations · 349 across the 25 of their papers we have counts for
5 papers · 1 filter
Robust Low-Complexity Randomized Methods for Locating Outliers in Large Matrices
Xingguo Li, Jarvis Haupt
This paper examines the problem of locating outlier columns in a large, otherwise low-rank matrix, in settings where {}{the data} are noisy, or where the overall matrix has missing…
Symmetry, Saddle Points, and Global Optimization Landscape of Nonconvex Matrix Factorization
Xingguo Li, Junwei Lu, Raman Arora +4
We propose a general theory for studying the \xl{landscape} of nonconvex \xl{optimization} with underlying symmetric structures \tz{for a class of machine learning problems (e.g.,…
On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
Xingguo Li, Tuo Zhao, Raman Arora +2
The cyclic block coordinate descent-type (CBCD-type) methods, which performs iterative updates for a few coordinates (a block) simultaneously throughout the procedure, have shown r…
On Fast Convergence of Proximal Algorithms for SQRT-Lasso Optimization: Don't Worry About Its Nonsmooth Loss Function
Xingguo Li, Haoming Jiang, Jarvis Haupt +4
Many machine learning techniques sacrifice convenient computational structures to gain estimation robustness and modeling flexibility. However, by exploring the modeling structures…
Nonconvex Sparse Learning via Stochastic Optimization with Progressive Variance Reduction
Xingguo Li, Raman Arora, Han Liu +2
We propose a stochastic variance reduced optimization algorithm for solving sparse learning problems with cardinality constraints. Sufficient conditions are provided, under which t…