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WWW
2009
ACM
14 years 8 months ago
Graffiti: node labeling in heterogeneous networks
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...
SIGMOD
2010
ACM
223views Database» more  SIGMOD 2010»
14 years 16 days ago
Finding maximal cliques in massive networks by H*-graph
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...
AI
2006
Springer
13 years 7 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
GRC
2008
IEEE
13 years 8 months ago
Effects of Varying the Delay Distribution in Random, Scale-free, and Small-world Networks
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...
Bum Soon Jang, Timothy Mann, Yoonsuck Choe
CISS
2008
IEEE
14 years 2 months ago
Distributed estimation in wireless sensor networks via variational message passing
Abstract – In this paper, a variational message passing framework is proposed for Markov random fields. Analogous to the traditional belief propagation algorithm, variational mes...
Yanbing Zhang, Huaiyu Dai