The sphere-concatenate method for gaussian process canonical correlation analysis

Authors:
Pei Ling Lai;Gayle Leen;Colin Fyfe
Affiliations:
Southern Taiwan Institute of Technology, Taiwan;Applied Computational Intelligence Research Unit, The University of Paisley, Scotland;Applied Computational Intelligence Research Unit, The University of Paisley, Scotland
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Year:
2006

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Abstract

We have recently developed several ways of using Gaussian Processes to perform Canonical Correlation Analysis. We review several of these methods, introduce a new way to perform Canonical Correlation Analysis with Gaussian Processes which involves sphering each data stream separately with probabilistic principal component analysis (PCA), concatenating the sphered data and re-performing probabilistic PCA. We also investigate the effect of sparsifying this last method. We perform a comparative study of these methods.