In this paper we present new methods for fast justification and propagation in the implication graph (IG) which is the core data structure of our SAT based implication engine. As ...
Stochastic models such as hidden Markov models or stochastic context free grammars can fail to return the correct, maximum likelihood solution in the case of semantic ambiguity. T...
In this paper, we propose a new method, Parametric Embedding (PE), for visualizing the posteriors estimated over a mixture model. PE simultaneously embeds both objects and their c...
Tomoharu Iwata, Kazumi Saito, Naonori Ueda, Sean S...
Deep Belief Networks (DBNs) are multi-layer generative models. They can be trained to model windows of coefficients extracted from speech and they discover multiple layers of fea...
Abdel-rahman Mohamed, Tara N. Sainath, George Dahl...
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...