Asymptotic performance of PCA for high-dimensional heteroscedastic data
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Principal Component Analysis (PCA) is a classical method for reducing the dimensionality of data by projecting them onto a subspace that captures most of their variation. Effective use of PCA in modern applications requires understanding its performance for da... ...
