Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
In pattern recognition systems, data fusion is an important issue and evidence theory is one such method that has been successful. Many researchers have proposed different rules fo...
Abstract. Event-B provides us with a powerful framework for correctby-construction system development. However, while developing dependable systems we should not only guarantee the...
This paper describes a novel approach to voice conversion using both a joint density model and a speaker model. In voice conversion studies, approaches based on Gaussian Mixture M...
Plan recognition is a form of abductive reasoning that involves inferring plans that best explain sets of observed actions. Most existing approaches to plan recognition and other ...