Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and
Robust Convergence Without the Condition Number

v1v2 (latest)

Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number

26 October 2020

ArXiv (abs)PDF HTML

Papers citing "Low-Rank Matrix Recovery with Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number"

15 / 15 papers shown

Title
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang Salar Fattahi Richard Y. Zhang 144 37 0 13 Apr 2025
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery Paris Giampouras HanQin Cai René Vidal 143 4 0 22 Oct 2024
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition Zhen Qin Zhihui Zhu 212 5 0 10 Jun 2024
Computationally Efficient and Statistically Optimal Robust High-Dimensional Linear Regression Yinan Shen Jingyang Li Jian-Feng Cai Dong Xia 59 1 0 10 May 2023
The Power of Preconditioning in Overparameterized Low-Rank Matrix Sensing Xingyu Xu Yandi Shen Yuejie Chi Cong Ma 122 37 0 02 Feb 2023
Deep Unfolded Tensor Robust PCA with Self-supervised Learning Harry Dong Megna Shah S. Donegan Yuejie Chi SSL 88 6 0 21 Dec 2022
Unrolling SVT to obtain computationally efficient SVT for n-qubit quantum state tomography S. Shanmugam Sheetal Kalyani 50 7 0 17 Dec 2022
Fast and Provable Tensor Robust Principal Component Analysis via Scaled Gradient Descent Harry Dong Tian Tong Cong Ma Yuejie Chi 89 14 0 18 Jun 2022
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization Yuetian Luo Xudong Li Anru R. Zhang 81 11 0 03 Aug 2021
GNMR: A provable one-line algorithm for low rank matrix recovery Pini Zilber B. Nadler 133 14 0 24 Jun 2021
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements Tian Tong Cong Ma Ashley Prater-Bennette Erin E. Tripp Yuejie Chi 108 33 0 29 Apr 2021
Spectral Methods for Data Science: A Statistical Perspective Yuxin Chen Yuejie Chi Jianqing Fan Cong Ma 153 173 0 15 Dec 2020
Recursive Importance Sketching for Rank Constrained Least Squares: Algorithms and High-order Convergence Yuetian Luo Wen Huang Xudong Li Anru R. Zhang 76 16 0 17 Nov 2020
Accelerating Ill-Conditioned Low-Rank Matrix Estimation via Scaled Gradient Descent Tian Tong Cong Ma Yuejie Chi 104 120 0 18 May 2020
Nonconvex Matrix Factorization from Rank-One Measurements Yuanxin Li Cong Ma Yuxin Chen Yuejie Chi 75 52 0 17 Feb 2018