We develop a semi-supervised learning method that constrains the posterior distribution of latent variables under a generative model to satisfy a rich set of feature expectation c...
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
Abstract. A paper document processing system is an information system component which transforms information on printed or handwritten documents into a computer-revisable form. In ...
Floriana Esposito, Donato Malerba, Francesca A. Li...
This paper presents a method for learning decision theoretic models of facial expressions and gestures from video data. We consider that the meaning of a facial display or gesture...