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

31 December 2020

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

2 / 2 papers shown

Title
Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay Yuetian Luo Anru R. Zhang 21 19 0 17 Jun 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