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AUSAI
2005
Springer
13 years 10 months ago
Conditioning Graphs: Practical Structures for Inference in Bayesian Networks
Abstract. Programmers employing inference in Bayesian networks typically rely on the inclusion of the model as well as an inference engine into their application. Sophisticated inf...
Kevin Grant, Michael C. Horsch
FEGC
2008
84views Biometrics» more  FEGC 2008»
13 years 6 months ago
Structure Inference of Bayesian Networks from Data: A New Approach Based on Generalized Conditional Entropy
We propose a novel algorithm for extracting the structure of a Bayesian network from a dataset. Our approach is based on generalized conditional entropies, a parametric family of e...
Dan A. Simovici, Saaid Baraty
JMLR
2010
102views more  JMLR 2010»
13 years 2 days ago
Efficient Algorithms for Conditional Independence Inference
The topic of the paper is computer testing of (probabilistic) conditional independence (CI) implications by an algebraic method of structural imsets. The basic idea is to transfor...
Remco R. Bouckaert, Raymond Hemmecke, Silvia Lindn...
BMCBI
2010
147views more  BMCBI 2010»
13 years 5 months ago
Learning biological network using mutual information and conditional independence
Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
IJON
2010
189views more  IJON 2010»
13 years 3 months ago
Inference and parameter estimation on hierarchical belief networks for image segmentation
We introduce a new causal hierarchical belief network for image segmentation. Contrary to classical tree structured (or pyramidal) models, the factor graph of the network contains...
Christian Wolf, Gérald Gavin