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Sparse Equisigned PCA: Algorithms and Performance Bounds in the Noisy Rank-1 ...
The dataset is used for estimating the sparse principal component based on different statistical criteria and proving sparsistency conditions. -
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... -
Non-negative rank-1 robust principal component analysis
The dataset is used to test the non-negative rank-1 robust principal component analysis (RPCA) algorithm.
