Low Rank Matrix Recovery via Robust Outlier Estimation
In practice, high-dimensional data are typically sampled from low-dimensional subspaces, but with intrusion of outliers and/or noises. Recovering the underlying structure and the pollution from the observations is of utmost importance to understanding the data. Besides properly modeling the subspace...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - (2018) vom: 12. Juli |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2018
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Online verfügbar |
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