Correntropy Based Matrix Completion

Yuning Yang, Yunlong Feng, Johan Suykens
2018 Entropy  
This paper studies the matrix completion problems when the entries are contaminated by non-Gaussian noise or outliers. The proposed approach employs a nonconvex loss function induced by the maximum correntropy criterion. With the help of this loss function, we develop a rank constrained, as well as a nuclear norm regularized model, which is resistant to non-Gaussian noise and outliers. However, its non-convexity also leads to certain difficulties. To tackle this problem, we use the simple
more » ... se the simple iterative soft and hard thresholding strategies. We show that when extending to the general affine rank minimization problems, under proper conditions, certain recoverability results can be obtained for the proposed algorithms. Numerical experiments indicate the improved performance of our proposed approach.
doi:10.3390/e20030171 pmid:33265262 fatcat:aqeqhe5mqzfvfbyi6zj7lg57oq