Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence

22 April 2019

Papers citing "Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence"

10 / 10 papers shown

Title
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization Cong Ma Xingyu Xu Tian Tong Yuejie Chi 16 9 0 09 Oct 2023
A Validation Approach to Over-parameterized Matrix and Image Recovery Lijun Ding Zhen Qin Liwei Jiang Jinxin Zhou Zhihui Zhu 40 13 0 21 Sep 2022
Low-Rank Mirror-Prox for Nonsmooth and Low-Rank Matrix Optimization Problems Dan Garber Atara Kaplan 16 0 0 23 Jun 2022
Robust Matrix Completion with Heavy-tailed Noise Bingyan Wang Jianqing Fan 21 3 0 09 Jun 2022
Low-Rank Extragradient Method for Nonsmooth and Low-Rank Matrix Optimization Problems Dan Garber Atara Kaplan 13 5 0 08 Feb 2022
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization Yuetian Luo Xudong Li Anru R. Zhang 23 9 0 03 Aug 2021
GNMR: A provable one-line algorithm for low rank matrix recovery Pini Zilber B. Nadler 43 13 0 24 Jun 2021
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence Yuetian Luo Wen Huang Xudong Li Anru R. Zhang 21 15 0 17 Nov 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 19 113 0 18 May 2020
Learning without Concentration S. Mendelson 80 334 0 01 Jan 2014