Dependency networks approximate a joint probability distribution over multiple random variables as a product of conditional distributions. Relational Dependency Networks (RDNs) are...
Sriraam Natarajan, Tushar Khot, Kristian Kersting,...
In recent years, with the rapid proliferation of digital images, the need to search and retrieve the images accurately, efficiently, and conveniently is becoming more acute. Automa...
In this paper we present a two-level generative model for representing the images and surface depth maps of drapery and clothes. The upper level consists of a number of folds whic...
Accurate unsupervised learning of phonemes of a language directly from speech is demonstrated via an algorithm for joint unsupervised learning of the topology and parameters of a ...
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...