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Informed Non-convex Robust Principal Component Analysis with Features

The dataset used in this paper is a low-rank matrix M, which can be decomposed into a low-rank component L∗ and a sparse error matrix S∗. The authors use this dataset to test their proposed algorithm for robust principal component analysis with features.

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Cite this as

Niannan Xue, Jiankang Deng, Yannis Panagakis, Stefanos Zafeiriou (2024). Dataset: Informed Non-convex Robust Principal Component Analysis with Features. https://doi.org/10.57702/30ojyuz4

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Additional Info

Field Value
Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.1709.04836
Author Niannan Xue
More Authors
Jiankang Deng
Yannis Panagakis
Stefanos Zafeiriou