Low-rank matrix recovery with Ky Fan 2-k-norm
Optimization and Control
2019-04-12 v1
Abstract
We propose Ky Fan 2-k-norm-based models for the nonconvex low-rank matrix recovery problem. A general difference of convex algorithm (DCA) is developed to solve these models. Numerical results show that the proposed models achieve high recoverability rates.
Keywords
Cite
@article{arxiv.1904.05590,
title = {Low-rank matrix recovery with Ky Fan 2-k-norm},
author = {Xuan Vinh Doan and Stephen Vavasis},
journal= {arXiv preprint arXiv:1904.05590},
year = {2019}
}
Comments
Accepted to WCGO 2019, 6th World Congress on Global Optimization, 8-10 July 2019