We consider two stochastic process methods for performing canonical correlation analysis (CCA). The first uses a Gaussian Process formulation of regression in which we use the cur...
Recently a class of multiscale stochastic models has been introducedin which Gaussian random processes are described by scale-recursive dynamics that are indexed by the nodes of a...
Paul W. Fieguth, William W. Irving, Alan S. Willsk...
We present a novel method for predictive modeling of human brain states from functional neuroimaging (fMRI) data. Extending the traditional canonical correlation analysis of discre...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
Abstract. We investigate a nonparametric model with which to visualize the relationship between two datasets. We base our model on Gaussian Process Latent Variable Models (GPLVM)[1...
This paper illustrates how canonical correlation analysis can be used for designing efficient visual operators by learning. The approach is highly task oriented and what constitute...