3 papers
stat.ML2021
Provable Low Rank Plus Sparse Matrix Separation Via Nonconvex Regularizers
April Sagan, John E. Mitchell
This paper considers a large class of problems where we seek to recover a low rank matrix and/or sparse vector from some set of measurements. While methods based on convex relaxati…
math.OC2020
Low-Rank Factorization for Rank Minimization with Nonconvex Regularizers
April Sagan, John E. Mitchell
Rank minimization is of interest in machine learning applications such as recommender systems and robust principal component analysis. Minimizing the convex relaxation to the rank…
math.OC2018
Solving Linear Programs with Complementarity Constraints using Branch-and-Cut
Bin Yu, John E. Mitchell, Jong-Shi Pang
A linear program with linear complementarity constraints (LPCC) requires the minimization of a linear objective over a set of linear constraints together with additional linear com…