We introduce a multi-label classification model and algorithm for labeling heterogeneous networks, where nodes belong to different types and different types have different sets of...
Ralitsa Angelova, Gjergji Kasneci, Fabian M. Sucha...
Maximal clique enumeration (MCE) is a fundamental problem in graph theory and has important applications in many areas such as social network analysis and bioinformatics. The prob...
James Cheng, Yiping Ke, Ada Wai-Chee Fu, Jeffrey X...
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Graph-theory-based approaches have been used with great success when analyzing abstract properties of natural and artificial networks. However, these approaches have not factored...
Abstract – In this paper, a variational message passing framework is proposed for Markov random fields. Analogous to the traditional belief propagation algorithm, variational mes...