On A Problem Of Weighted Low-Rank Approximation Of Matrices

Keywords

Alternating direc-tion method; Singular value decomposition; Weighted low-rank approximation

Abstract

We study a weighted low-rank approximation that is inspired by a problem of constrained low-rank approximation of matrices as initiated by the work of Golub, Hoffman, and Stewart [Linear Algebra Appl., 88/89 (1987), pp. 317-327]. Our results reduce to that of Golub, Ho-man, and Stewart in the limiting cases. We also propose an algorithm based on the alternating direction method to solve our weighted low-rank approximation problem and compare it with the state-of-Art general algorithms such as the weighted total alternating least squares algorithm and the expectation maximization algorithm.

Publication Date

1-1-2017

Publication Title

SIAM Journal on Matrix Analysis and Applications

Volume

38

Issue

2

Number of Pages

530-553

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1137/15M1043145

Socpus ID

85021705173 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85021705173

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