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ICDM
2007
IEEE
153views Data Mining» more  ICDM 2007»
15 years 11 months ago
HSN-PAM: Finding Hierarchical Probabilistic Groups from Large-Scale Networks
Real-world social networks are often hierarchical, reflecting the fact that some communities are composed of a few smaller, sub-communities. This paper describes a hierarchical B...
Haizheng Zhang, Wei Li, Xuerui Wang, C. Lee Giles,...
ICML
1996
IEEE
16 years 5 months ago
Discretizing Continuous Attributes While Learning Bayesian Networks
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Moisés Goldszmidt, Nir Friedman
MOBIHOC
2009
ACM
16 years 5 months ago
Multicasting in delay tolerant networks: a social network perspective
Node mobility and end-to-end disconnections in Delay Tolerant Networks (DTNs) greatly impair the effectiveness of data dissemination. Although social-based approaches can be used ...
Wei Gao, Qinghua Li, Bo Zhao, Guohong Cao
ISBI
2011
IEEE
14 years 8 months ago
Sparse topological data recovery in medical images
For medical image analysis, the test statistic of the measurements is usually constructed at every voxels in space and thresholded to determine the regions of significant signals...
Moo K. Chung, Hyekyoung Lee, Peter T. Kim, Jong Ch...
CIDM
2009
IEEE
15 years 11 months ago
A new hybrid method for Bayesian network learning With dependency constraints
Abstract— A Bayes net has qualitative and quantitative aspects: The qualitative aspect is its graphical structure that corresponds to correlations among the variables in the Baye...
Oliver Schulte, Gustavo Frigo, Russell Greiner, We...