clustering of documents according to sharing of topics at multiple levels of abstraction. Given a corpus of documents, a posterior inference algorithm finds an approximation to a ...
David M. Blei, Thomas L. Griffiths, Michael I. Jor...
This paper presents a new deterministic approximation technique in Bayesian networks. This method, "Expectation Propagation," unifies two previous techniques: assumed-de...
This paper addresses the problem of fully automated
mining of public space video data. A novel Markov Clustering
Topic Model (MCTM) is introduced which builds on
existing Dynami...
A statistical framework for modeling and prediction of binary matrices is presented. The method is applied to social network analysis, specifically the database of US Supreme Cou...
Eric Wang, Jorge Silva, Rebecca Willett, Lawrence ...
Background: With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few appro...
Grace S. Shieh, Chung-Ming Chen, Ching-Yun Yu, Jui...