Details

Autor(en) / Beteiligte

• Yang, Yuning
• Feng, Yunlong
• Suykens, Johan

Titel

Correntropy Based Matrix Completion

Ist Teil von

• Entropy (Basel, Switzerland), 2018-03, Vol.20 (3), p.171

Ort / Verlag

Basel: MDPI AG

Erscheinungsjahr

2018

Link zum Volltext

Quelle

EZB Electronic Journals Library

Beschreibungen/Notizen

• 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 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.