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- Title
Correntropy Based Matrix Completion.
- Authors
Yang, Yuning; Feng, Yunlong; Suykens, Johan A. K.
- Abstract
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.
- Subjects
ENTROPY; MATRICES (Mathematics); LOSS functions (Statistics); RANDOM noise theory; OUTLIERS (Statistics); COMPUTER algorithms; MATHEMATICAL models
- Publication
Entropy, 2018, Vol 20, Issue 3, p171
- ISSN
1099-4300
- Publication type
Article
- DOI
10.3390/e20030171