Optimally Weighted PCA for High-Dimensional Heteroscedastic Data
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Modern data are increasingly both high-dimensional and heteroscedastic. This paper considers the challenge of estimating underlying principal components from high-dimensional data with noise that is heteroscedastic across samples, i.e., some samples are noisie... ...
