Generalized singular value thresholding operator to affine matrix rank minimization problem
Optimization and Control
2018-04-24 v3
Abstract
It is well known that the affine matrix rank minimization problem is NP-hard and all known algorithms for exactly solving it are doubly exponential in theory and in practice due to the combinational nature of the rank function. In this paper, a generalized singular value thresholding operator is generated to solve the affine matrix rank minimization problem. Numerical experiments show that our algorithm performs effectively in finding a low-rank matrix compared with some state-of-art methods.
Keywords
Cite
@article{arxiv.1707.00573,
title = {Generalized singular value thresholding operator to affine matrix rank minimization problem},
author = {Angang Cui and Haiyang Li and Jigen Peng and Junxiong Jia},
journal= {arXiv preprint arXiv:1707.00573},
year = {2018}
}