Shrinkage Function And Its Applications In Matrix Approximation
Keywords
Low-rank approximation; Shrinkage function; Singular value decomposition; Sparse approximation
Abstract
The shrinkage function is widely used in matrix low-rank approximation, compressive sensing, and statistical estimation. In this article, an elementary derivation of the shrinkage function is given. In addition, applications of the shrinkage function are demonstrated in solving several well-known problems, together with a new result in matrix approximation.
Publication Date
5-1-2017
Publication Title
Electronic Journal of Linear Algebra
Volume
32
Number of Pages
163-171
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.13001/1081-3810.3218
Copyright Status
Unknown
Socpus ID
85020864444 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85020864444
STARS Citation
Boas, Toby; Dutta, Aritra; Li, Xin; Mercier, Kathryn P.; and Niderman, Eric, "Shrinkage Function And Its Applications In Matrix Approximation" (2017). Scopus Export 2015-2019. 5342.
https://stars.library.ucf.edu/scopus2015/5342