Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Equivalence and synthesis of causal models
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Improved learning of Bayesian networks
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Optimal structure identification with greedy search
The Journal of Machine Learning Research
Probabilistic Conditional Independence Structures: With 42 Illustrations (Information Science and Statistics)
A graphical characterization of the largest chain graphs
International Journal of Approximate Reasoning
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
A transformational characterization of equivalent Bayesian network structures
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Causal inference and causal explanation with background knowledge
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
A Graphical Representation of Equivalence Classes of AMP Chain Graphs
The Journal of Machine Learning Research
A reconstruction algorithm for the essential graph
International Journal of Approximate Reasoning
Characterization of inclusion neighbourhood in terms of the essential graph
International Journal of Approximate Reasoning
Learning Bayesian network structure: Towards the essential graph by integer linear programming tools
International Journal of Approximate Reasoning
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Standard methods for solving influence diagrams consist in stepwise elimination of variables, and along with elimination of a variable a set of new potentials over new domains is calculated. It is well known that these methods tend to produce unnecessarily ...