How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing:
The Curses of Symmetry and Initialization

v1v2v3 (latest)

How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization

3 October 2023

ArXiv (abs)PDF HTML

Papers citing "How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization"

7 / 7 papers shown

Title
PoLAR: Polar-Decomposed Low-Rank Adapter Representation Kai Lion Liang Zhang Bingcong Li Niao He 58 0 0 03 Jun 2025
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang Salar Fattahi Richard Y. Zhang 147 37 0 13 Apr 2025
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery Paris Giampouras HanQin Cai René Vidal 147 4 0 22 Oct 2024
Toward Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixture Models Weihang Xu Maryam Fazel S. Du 91 2 0 29 Jun 2024
Low-Tubal-Rank Tensor Recovery via Factorized Gradient Descent Zhiyu Liu Zhi Han Yandong Tang Xi-Le Zhao Yao Wang 179 1 0 22 Jan 2024
A Validation Approach to Over-parameterized Matrix and Image Recovery Lijun Ding Zhen Qin Liwei Jiang Jinxin Zhou Zhihui Zhu 113 14 0 21 Sep 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang Salar Fattahi Richard Y. Zhang 163 24 0 07 Jun 2022