Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
We present a new method for establishing an alignment between a polyphonic musical score and a corresponding sampled audio performance. The method uses a graphical model containin...
We propose a generative statistical approach to human motion modeling and tracking that utilizes probabilistic latent semantic (PLSA) models to describe the mapping of image featu...