Statistical analysis with missing data
Statistical analysis with missing data
The EM algorithm for graphical association models with missing data
Computational Statistics & Data Analysis - Special issue dedicated to Toma´sˇ Havra´nek
Uniform Crossover in Genetic Algorithms
Proceedings of the 3rd International Conference on Genetic Algorithms
An Analysis of the Interacting Roles of Population Size and Crossover in Genetic Algorithms
PPSN I Proceedings of the 1st Workshop on Parallel Problem Solving from Nature
The Bayesian structural EM algorithm
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Fusion of domain knowledge with data for structural learning in object oriented domains
The Journal of Machine Learning Research
Learning Bayesian Networks from Incomplete Data Based on EMI Method
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Learning Functional Dependency Networks Based on Genetic Programming
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
The Journal of Machine Learning Research
Learning Bayesian Networks Based on a Mutual Information Scoring Function and EMI Method
ISNN '07 Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks
Exploiting Data Missingness in Bayesian Network Modeling
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
Journal of Artificial Intelligence Research
IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
Learning Bayesian networks with combination of MRMR criterion and EMI method
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
A parallel algorithm for learning Bayesian networks
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Learning Bayesian networks using evolutionary algorithm and a variant of MDL score
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
Learning Bayesian network structure from incomplete data without any assumption
DASFAA'08 Proceedings of the 13th international conference on Database systems for advanced applications
Combinatorial optimization by learning and simulation of Bayesian networks
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
Review: learning bayesian networks: Approaches and issues
The Knowledge Engineering Review
A review on evolutionary algorithms in Bayesian network learning and inference tasks
Information Sciences: an International Journal
Learning Bayesian network classifiers from label proportions
Pattern Recognition
Learning optimal bayesian networks: a shortest path perspective
Journal of Artificial Intelligence Research
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This paper describes stochastic search approaches, including a new stochastic algorithm and an adaptive mutation operator, for learning Bayesian networks from incomplete data. This problem is characterized by a huge solution space with a highly multimodal landscape. State-of-the-art approaches all involve using deterministic approaches such as the elrpectation-maximization algorithm. These approaches are guaranteed to find local maxima, but do not explore the landscape for other modes. Our approach evolves structure and the missing data. We compare our stochastic algorithms and show they all produce accurate results.