You're currently viewing an old version of this dataset. To see the current version, click here.

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.

Data and Resources

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

DOI retrieved: December 16, 2024

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