In this paper, we present a method for predictive modeling of anatomic structures using canonical correlation analysis (CCA). Using this technique, certain anatomical structures, ...
We introduce a mixture of probabilistic canonical correlation analyzers model for analyzing local correlations, or more generally mutual statistical dependencies, in cooccurring d...
Clustering data in high dimensions is believed to be a hard problem in general. A number of efficient clustering algorithms developed in recent years address this problem by proje...
Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu,...
A fast exploratory framework for extracting cardiac noise signals contained in rest-case fMRI images is presented. Highly autocorrelated, independent components of the input time ...
In this paper, we apply a multiple regression method based on Canonical Correlation Analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the corre...
Michael Reiter, Rene Donner, Georg Langs, Horst Bi...
It has previously been shown that canonical correlation analysis (CCA) works well for detecting neural activity in fMRI data. This is due to the ability of CCA to perform simultan...
We introduce a new framework, namely Tensor Canonical Correlation Analysis (TCCA) which is an extension of classical Canonical Correlation Analysis (CCA) to multidimensional data ...