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Fast Global Convergence for Low-rank Matrix Recovery via Riemannian
  Gradient Descent with Random Initialization
v1v2 (latest)

Fast Global Convergence for Low-rank Matrix Recovery via Riemannian Gradient Descent with Random Initialization

31 December 2020
Daniel Leibovici
Zhenzhen Li
Ziyun Zhang
ArXiv (abs)PDFHTML

Papers citing "Fast Global Convergence for Low-rank Matrix Recovery via Riemannian Gradient Descent with Random Initialization"

8 / 8 papers shown
Riemannian Bilevel Optimization
Riemannian Bilevel Optimization
Sanchayan Dutta
Xiang Cheng
S. Sra
292
0
0
22 May 2024
Acceleration and Implicit Regularization in Gaussian Phase Retrieval
Acceleration and Implicit Regularization in Gaussian Phase RetrievalInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023
Tyler Maunu
M. Molina-Fructuoso
355
1
0
21 Nov 2023
Tensor-on-Tensor Regression: Riemannian Optimization,
  Over-parameterization, Statistical-computational Gap, and Their Interplay
Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their InterplayAnnals of Statistics (Ann. Stat.), 2022
Yuetian Luo
Anru R. Zhang
364
27
0
17 Jun 2022
On Geometric Connections of Embedded and Quotient Geometries in
  Riemannian Fixed-rank Matrix Optimization
On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix OptimizationMathematics of Operations Research (MOR), 2021
Yuetian Luo
Xudong Li
Xinmiao Zhang
364
6
0
23 Oct 2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent
  in Low-rank Matrix Optimization
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization
Yuetian Luo
Xudong Li
Anru R. Zhang
364
11
0
03 Aug 2021
Asymptotic Escape of Spurious Critical Points on the Low-rank Matrix
  Manifold
Asymptotic Escape of Spurious Critical Points on the Low-rank Matrix Manifold
Daniel Leibovici
Zhenzhen Li
Ziyun Zhang
237
2
0
20 Jul 2021
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical
  Optimality and Second-Order Convergence
Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order ConvergenceJournal of machine learning research (JMLR), 2021
Yuetian Luo
Anru R. Zhang
497
27
0
24 Apr 2021
Riemannian Perspective on Matrix Factorization
Riemannian Perspective on Matrix Factorization
Kwangjun Ahn
Felipe Suarez
153
13
0
01 Feb 2021
1
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