It is well known that among all probabilistic graphical Markov models the class of decomposable models is the most advantageous in the sense that the respective distributions can b...
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,...
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
In this paper, we study probabilistic modeling of heterogeneously attributed multi-dimensional arrays. The model can manage the heterogeneity by employing an individual exponential...
— The paper presents IRIS, an Integrated Routing and Interest dissemination System for wireless sensor networks. The proposed protocols are designed to work under very low duty c...