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A pseudo-heuristic parameter selection rule for [formula omitted]-regularized minimization problems.
- Source :
-
Journal of Computational & Applied Mathematics . May2018, Vol. 333, p1-19. 19p. - Publication Year :
- 2018
-
Abstract
- This paper considers the regularization parameter determination of l 1 -regularized minimization problem. We solve the l 1 -regularized problem using iterative reweighted least squares (IRLS) which involves solving a linear system whose coefficient matrix has the form α M + ( 1 − α ) N ( α ∈ ( 0 , 1 ) ). The aim of this paper is to find an efficient and computationally inexpensive algorithm to both choose the regularization parameter and solve the l 1 -regularized problem. In order to achieve this, we propose an IRLS algorithm with adaptive regularization parameter selection based on a heuristic parameter determination rule—de Boor’s parameter selection criterion. Compared with some of the state-of-the-art algorithms and parameter selection rules, the numerical experiments show the efficiency and robustness of the proposed method. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03770427
- Volume :
- 333
- Database :
- Academic Search Index
- Journal :
- Journal of Computational & Applied Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 127137567
- Full Text :
- https://doi.org/10.1016/j.cam.2017.10.006