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A Dual Formulation for Probabilistic Principal Component Analysis

07/19/2023

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by Henri De Plaen, et al.

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In this paper, we characterize Probabilistic Principal Component Analysis in Hilbert spaces and demonstrate how the optimal solution admits a representation in dual space. This allows us to develop a generative framework for kernel methods. Furthermore, we show how it englobes Kernel Principal Component Analysis and illustrate its working on a toy and a real dataset.

Henri De Plaen
3 publications
Johan A. K. Suykens
61 publications

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