Matrix completion via a low rank factorization model and an augmented Lagrangean succesive overrelaxation algorithm

zbMath1398.65082MaRDI QIDQ1653941

Jinjun Yuan, Harry Oviedo, Hugo J. Lara

Publication date: 7 August 2018

Published in: Bulletin of Computational Applied Mathematics (Search for Journal in Brave)

Full work available at URL: http://drive.google.com/open?id=0B5GyVVQ6O030bEVPb3owckh5YVE

zbMATH Keywords

matrix completionnonlinear SOR methodaugmented Lagrange methodnonlinear Gauss-Seidel methodalternanting minimization

Mathematics Subject Classification ID

Iterative numerical methods for linear systems (65F10) Matrix completion problems (15A83)

Related Items (2)

Implicit steepest descent algorithm for optimization with orthogonality constraints ⋮ Global convergence of Riemannian line search methods with a Zhang-Hager-type condition

Uses Software

• ALGENCAN
• Eigentaste

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm
• On the convergence of the block nonlinear Gauss-Seidel method under convex constraints
• Exact matrix completion via convex optimization
• Practical Augmented Lagrangian Methods for Constrained Optimization

This page was built for publication: Matrix completion via a low rank factorization model and an augmented Lagrangean succesive overrelaxation algorithm