Learning belief networks from data: an information theory based approach
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Learning Bayesian networks from data: an information-theory based approach
Artificial Intelligence
Learning Structure from Data and Its Application to Ozone Prediction
Applied Intelligence
Constructing Efficient Belief Network Structures With Expert Provided Information
IEEE Transactions on Knowledge and Data Engineering
A Guide to the Literature on Learning Probabilistic Networks from Data
IEEE Transactions on Knowledge and Data Engineering
Current Approaches to Handling Imperfect Information in Data and Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
A Formalism for Building Causal Polytree Structures Using Data Distributions
ISMIS '00 Proceedings of the 12th International Symposium on Foundations of Intelligent Systems
A formal approach to using data distributions for building causal polytree structures
Information Sciences—Informatics and Computer Science: An International Journal
Supporting the construction of explanation models and diagnostic reasoning in probabilistic domains
ICLS '96 Proceedings of the 1996 international conference on Learning sciences
Bayesian learning of Bayesian networks with informative priors
Annals of Mathematics and Artificial Intelligence
Criteria to evaluate approximate belief network representations in expert systems
Decision Support Systems
Modelling multiple-classifier relationships using Bayesian belief networks
MCS'07 Proceedings of the 7th international conference on Multiple classifier systems
A construction of Bayesian networks from databases based on an MDL principle
UAI'93 Proceedings of the Ninth international conference on Uncertainty in artificial intelligence
Theory refinement on Bayesian networks
UAI'91 Proceedings of the Seventh conference on Uncertainty in Artificial Intelligence
A Bayesian method for constructing Bayesian belief networks from databases
UAI'91 Proceedings of the Seventh conference on Uncertainty in Artificial Intelligence
Expert Systems with Applications: An International Journal
Using literature and data to learn Bayesian networks as clinical models of ovarian tumors
Artificial Intelligence in Medicine
Learning bayesian networks from Markov random fields: An efficient algorithm for linear models
ACM Transactions on Knowledge Discovery from Data (TKDD)
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