Orthogonal Rank-One Matrix Pursuit for Low Rank Matrix Completion
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Publication:5251927
DOI10.1137/130934271zbMath1315.65044arXiv1404.1377OpenAlexW2001114276MaRDI QIDQ5251927
Jieping Ye, Hasan Davulcu, Zhaosong Lu, Zheng Wang, Wei Fan, Ming-Jun Lai
Publication date: 21 May 2015
Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1404.1377
algorithmconvergencesingular value decompositionmatrix completionnumerical resultrank minimizationlow rankmatching pursuit
Numerical solutions to overdetermined systems, pseudoinverses (65F20) Iterative numerical methods for linear systems (65F10) Matrix completion problems (15A83)
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Cites Work
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- An implementable proximal point algorithmic framework for nuclear norm minimization
- A coordinate gradient descent method for \(\ell_{1}\)-regularized convex minimization
- Fixed point and Bregman iterative methods for matrix rank minimization
- Estimation of (near) low-rank matrices with noise and high-dimensional scaling
- Convex multi-task feature learning
- CoSaMP: Iterative signal recovery from incomplete and inaccurate samples
- Some remarks on greedy algorithms
- Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm
- Parallel stochastic gradient algorithms for large-scale matrix completion
- Coordinate descent algorithms for lasso penalized regression
- Exact matrix completion via convex optimization
- Improved Iteratively Reweighted Least Squares for Unconstrained Smoothed $\ell_q$ Minimization
- A Singular Value Thresholding Algorithm for Matrix Completion
- Greed is Good: Algorithmic Results for Sparse Approximation
- Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization
- Greedy approximation
- The Orthogonal Super Greedy Algorithm and Applications in Compressed Sensing
- ADMiRA: Atomic Decomposition for Minimum Rank Approximation
- Low-Rank Optimization with Trace Norm Penalty
- Sparse Approximate Solutions to Semidefinite Programs
- Low-rank matrix completion using alternating minimization
