306 citations · 1.5k across the 93 of their papers we have counts for
5 papers · 1 filter
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis +1
We consider the non-square matrix sensing problem, under restricted isometry property (RIP) assumptions. We focus on the non-convex formulation, where any rank- matrix $X \in \m…
Solving a Mixture of Many Random Linear Equations by Tensor Decomposition and Alternating Minimization
Xinyang Yi, Constantine Caramanis, Sujay Sanghavi
We consider the problem of solving mixed random linear equations with components. This is the noiseless setting of mixed linear regression. The goal is to estimate multiple lin…
Finding Low-Rank Solutions via Non-Convex Matrix Factorization, Efficiently and Provably
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis +1
A rank- matrix can be written as a product , where and . One could explo…
Provable Burer-Monteiro factorization for a class of norm-constrained matrix problems
Dohyung Park, Anastasios Kyrillidis, Srinadh Bhojanapalli +2
We study the projected gradient descent method on low-rank matrix problems with a strongly convex objective. We use the Burer-Monteiro factorization approach to implicitly enforce…
Fast Algorithms for Robust PCA via Gradient Descent
Xinyang Yi, Dohyung Park, Yudong Chen +1
We consider the problem of Robust PCA in the fully and partially observed settings. Without corruptions, this is the well-known matrix completion problem. From a statistical standp…