A new complexity metric for nonconvex rank-one generalized matrix completion
From MaRDI portal
Publication:6608034
DOI10.1007/s10107-023-02008-5zbMATH Open1547.65048MaRDI QIDQ6608034
Hai-xiang Zhang, Baturalp Yalcin, Javad Lavaei, Somayeh Sojoudi
Publication date: 19 September 2024
Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)
Numerical mathematical programming methods (65K05) Nonconvex programming, global optimization (90C26) Matrix completion problems (15A83) Numerical methods for low-rank matrix approximation; matrix compression (65F55)
Cites Work
- Unnamed Item
- Unnamed Item
- Adaptive cubic regularisation methods for unconstrained optimization. I: Motivation, convergence and numerical results
- A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization
- A geometric analysis of phase retrieval
- Linear programming, complexity theory and elementary functional analysis
- Bridging convex and nonconvex optimization in robust PCA: noise, outliers and missing data
- Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
- Guarantees of Riemannian optimization for low rank matrix completion
- Gradient descent with random initialization: fast global convergence for nonconvex phase retrieval
- Exact matrix completion via convex optimization
- Guarantees of Riemannian Optimization for Low Rank Matrix Recovery
- Guaranteed Matrix Completion via Non-Convex Factorization
- Phase Retrieval via Wirtinger Flow: Theory and Algorithms
- Complete Dictionary Recovery Over the Sphere I: Overview and the Geometric Picture
- Robust principal component analysis?
- Learning Sparsely Used Overcomplete Dictionaries via Alternating Minimization
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- Global Optimality in Low-Rank Matrix Optimization
- Condition Numbers, the Barrier Method, and the Conjugate-Gradient Method
- Turan's Graph Theorem
- Scalable Semidefinite Programming
- Low-Rank Matrix Recovery With Scaled Subgradient Methods: Fast and Robust Convergence Without the Condition Number
- Nonconvex Rectangular Matrix Completion via Gradient Descent Without ℓ₂,∞ Regularization
- Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization
- Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery
- Model-free Nonconvex Matrix Completion: Local Minima Analysis and Applications in Memory-efficient Kernel PCA
- Nonconvex Robust Low-Rank Matrix Recovery
- Nonconvex Optimization Meets Low-Rank Matrix Factorization: An Overview
- Tight Oracle Inequalities for Low-Rank Matrix Recovery From a Minimal Number of Noisy Random Measurements
- The Power of Convex Relaxation: Near-Optimal Matrix Completion
- Low-rank matrix completion using alternating minimization
This page was built for publication: A new complexity metric for nonconvex rank-one generalized matrix completion