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
Copyright Status
Unknown
Socpus ID
85021705173 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85021705173
STARS Citation
Dutta, Aritra and Li, Xin, "On A Problem Of Weighted Low-Rank Approximation Of Matrices" (2017). Scopus Export 2015-2019. 5978.
https://stars.library.ucf.edu/scopus2015/5978