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» Kronecker Graphs: An Approach to Modeling Networks
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FUZZIEEE
2007
IEEE
14 years 3 months ago
Learning Undirected Possibilistic Networks with Conditional Independence Tests
—Approaches based on conditional independence tests are among the most popular methods for learning graphical models from data. Due to the predominance of Bayesian networks in th...
Christian Borgelt
COMPSAC
2008
IEEE
14 years 3 months ago
Measuring Network Security Using Bayesian Network-Based Attack Graphs
Given the increasing dependence of our societies on information systems, the overall security of these systems should be measured and improved. Existing work generally focuses on ...
Marcel Frigault, Lingyu Wang
CIBCB
2006
IEEE
14 years 2 months ago
A Novel Graphical Model Approach to Segmenting Cell Images
— Successful biological image analysis usually requires satisfactory segmentations to identify regions of interest as an intermediate step. Here we present a novel graphical mode...
Shann-Ching Chen, Ting Zhao, Geoffrey J. Gordon, R...
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
14 years 2 months ago
Mining closed relational graphs with connectivity constraints
Relational graphs are widely used in modeling large scale networks such as biological networks and social networks. In this kind of graph, connectivity becomes critical in identif...
Xifeng Yan, Xianghong Jasmine Zhou, Jiawei Han
APWEB
2008
Springer
13 years 10 months ago
The Layered World of Scientific Conferences
Recent models have introduced the notion of dimensions and hierarchies in social networks. These models motivate the mining of small world graphs under a new perspective. We exempl...
Michael Kuhn 0002, Roger Wattenhofer