Generalized Principal Component Analysis

Published 3 Jul 2019 in cs.LG and stat.ML | (1907.02647v1)

Abstract: Generalized principal component analysis (GLM-PCA) facilitates dimension reduction of non-normally distributed data. We provide a detailed derivation of GLM-PCA with a focus on optimization. We also demonstrate how to incorporate covariates, and suggest post-processing transformations to improve interpretability of latent factors.

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Authors (1)

F. William Townes

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