This paper presents a theoretical study of decentralized control for sensing-based shape formation on modular multirobot systems, where the desired shape is specified in terms of ...
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
The contemporary high-speed networks, e.g. the Internet and asynchronous transfer mode (ATM) networks provide a convenient and cost-effective communication platform to carry the e...
We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
Modeling the evolution of topics with time is of great value in automatic summarization and analysis of large document collections. In this work, we propose a new probabilistic gr...
Ramesh Nallapati, Susan Ditmore, John D. Lafferty,...