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ICDM
2005
IEEE
116views Data Mining» more  ICDM 2005»
15 years 5 months ago
Learning Functional Dependency Networks Based on Genetic Programming
Bayesian Network (BN) is a powerful network model, which represents a set of variables in the domain and provides the probabilistic relationships among them. But BN can handle dis...
Wing-Ho Shum, Kwong-Sak Leung, Man Leung Wong
UAI
1997
15 years 28 days ago
Object-Oriented Bayesian Networks
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
Daphne Koller, Avi Pfeffer
FLAIRS
2007
15 years 1 months ago
System Diagnosability Analysis Using p-slop MAP
Researchers have reported successful deployments of diagnosis decision support systems based on Bayesian networks. However, the methodology for evaluating the diagnosability for s...
Tsai-Ching Lu, K. Wojtek Przytula
JMLR
2006
169views more  JMLR 2006»
14 years 11 months ago
Bayesian Network Learning with Parameter Constraints
The task of learning models for many real-world problems requires incorporating domain knowledge into learning algorithms, to enable accurate learning from a realistic volume of t...
Radu Stefan Niculescu, Tom M. Mitchell, R. Bharat ...
PKDD
2010
Springer
148views Data Mining» more  PKDD 2010»
14 years 10 months ago
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
Abstract. A new method is proposed for compiling causal independencies into Markov logic networks (MLNs). An MLN can be viewed as compactly representing a factorization of a joint ...
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasa...