We present a variational Bayesian framework for performing inference, density estimation and model selection in a special class of graphical models--Hidden Markov Random Fields (H...
Li Cheng, Feng Jiao, Dale Schuurmans, Shaojun Wang
The Sesame modeling and simulation framework aims at early and thus efficient system-level design space exploration of embedded multimedia system architectures. So far, Sesame onl...
Abstract. In this paper, we introduce an adaptive model-based segmentation framework, in which edge and region information are integrated and used adaptively while a solid model de...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas,...
Abstract. Nowadays, information systems have to perform in complex, heterogeneous environments, considering a variety of system users with different needs and preferences. Software...
Mirko Morandini, Loris Penserini, Anna Perini, Ang...
Bayesian networks are commonly used in cognitive student modeling and assessment. They typically represent the item-concepts relationships, where items are observable responses to ...