SuperPCA: subspace analysis and an efficient algorithm for high-dimensional PCA
arXiv:2609.26406v1 Announce Type: new Abstract: Principal component analysis (PCA) is a fundamental tool to reduce the dimensionality of the data in many applications. PCA finds a few signal directions that contain most of the variability of the data by computing the eigenvectors of the sample cova…
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- 2026-09-24 04:00 · arXiv stat.ML
SuperPCA: subspace analysis and an efficient algorithm for high-dimensional PCA