| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4946560 | Neural Networks | 2017 | 25 Pages |
Abstract
We propose a robust Alternating Low-Rank Representation (ALRR) model formed by an alternating forward-backward representation process. For forward representation, ALRR first recovers the low-rank PCs and random corruptions by an adaptive local Robust PCA (RPCA). Then, ALRR performs a joint Lp-norm and L2,p-norm minimization (0
Related Topics
Physical Sciences and Engineering
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Artificial Intelligence
Authors
Zhao Zhang, Mingbo Zhao, Fanzhang Li, Li Zhang, Shuicheng Yan,