Robust Recovery of Corrupted Low-RankMatrix by Implicit Regularizers
Low-rank matrix recovery algorithms aim to recover a corrupted low-rank matrix with sparse errors. However, corrupted errors may not be sparse in real-world problems and the relationship between ℓ1 regularizer on noise and robust M-estimators is still unknown. This paper proposes a general robust fr...
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 36(2014), 4 vom: 01. Apr., Seite 770-83 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2014
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence |
| Schlagworte: | Journal Article Research Support, Non-U.S. Gov't |
| Online verfügbar |
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