Low-rank matrix recovery with Ky Fan 2-k-norm

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.

arXiv commentAccepted to WCGO 2019, 6th World Congress on Global Optimization, 8-10 July 2019