Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
We present a novel algorithm for agglomerative hierarchical clustering based on evaluating marginal likelihoods of a probabilistic model. This algorithm has several advantages ove...
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
This paper describes the creation of an interactive audience voting system, iVo. The device is intended for diving and gymnastics events during the 2004 Summer Olympics in Athens,...