Shrinkage function and its applications in matrix approximation

DOI10.13001/1081-3810.3218zbMATH Open1376.65046arXiv1601.07600OpenAlexW2963998230MaRDI QIDQ4594671

Xin Li, Eric Niderman, Katie Mercier, Aritra Dutta, Toby Boas

Publication date: 24 November 2017

Published in: The Electronic Journal of Linear Algebra (Search for Journal in Brave)

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.

Full work available at URL: https://arxiv.org/abs/1601.07600

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zbMATH Keywords

singular value decomposition sparse approximation low-rank approximation shrinkage function

Mathematics Subject Classification ID

Computational methods for sparse matrices (65F50) Factorization of matrices (15A23) Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Numerical computation of matrix norms, conditioning, scaling (65F35)

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