Back to Search
Start Over
A reweighted nuclear norm minimization algorithm for low rank matrix recovery.
- Source :
-
Journal of Computational & Applied Mathematics . Jun2014, Vol. 263, p338-350. 13p. - Publication Year :
- 2014
-
Abstract
- Abstract: In this paper, we propose a reweighted nuclear norm minimization algorithm based on the weighted fixed point method (RNNM–WFP algorithm) to recover a low rank matrix, which iteratively solves an unconstrained minimization problem introduced as a nonconvex smooth approximation of the low rank matrix minimization problem. We prove that any accumulation point of the sequence generated by the RNNM–WFP algorithm is a stationary point of the minimization problem. Numerical experiments on randomly generated matrix completion problems indicate that the proposed algorithm has better recoverability compared to existing iteratively reweighted algorithms. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 03770427
- Volume :
- 263
- Database :
- Academic Search Index
- Journal :
- Journal of Computational & Applied Mathematics
- Publication Type :
- Academic Journal
- Accession number :
- 94308231
- Full Text :
- https://doi.org/10.1016/j.cam.2013.12.005