Solving a low-rank factorization model for matrix completion by a nonlinear successive over-relaxation algorithm

The matrix completion problem is to recover a low-rank matrix from a subset of its entries. The main solution strategy for this problem has been based on nuclear-norm minimization which requires computing singular value decompositions—a task that is increasingly costly as matrix sizes and ranks incr...

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Bibliographic Details

Published in:	Mathematical programming computation Vol. 4; no. 4; pp. 333 - 361
Main Authors:	Wen, Zaiwen, Yin, Wotao, Zhang, Yin
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer-Verlag 01.12.2012
Subjects:	Full Length Paper Mathematics Mathematics and Statistics Mathematics of Computing Operations Research/Decision Theory Optimization Theory of Computation 65K05 90C06 Alternating minimization Nonlinear GS method 93C41 68Q32 Nonlinear SOR method Matrix completion
ISSN:	1867-2949, 1867-2957
Online Access:	Get full text
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