Theory refinement on Bayesian networks
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
The EM algorithm for graphical association models with missing data
Computational Statistics & Data Analysis - Special issue dedicated to Toma´sˇ Havra´nek
Learning Belief Networks in the Presence of Missing Values and Hidden Variables
ICML '97 Proceedings of the Fourteenth International Conference on Machine Learning
Local learning in probabilistic networks with hidden variables
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Learning Bayesian networks with local structure
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Asymptotic model selection for directed networks with hidden variables*
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Using new data to refine a Bayesian network
UAI'94 Proceedings of the Tenth international conference on Uncertainty in artificial intelligence
Application of Bayesian Network Learning Methods to Waste Water Treatment Plants
Applied Intelligence
Incremental Learning of Tree Augmented Naive Bayes Classifiers
IBERAMIA 2002 Proceedings of the 8th Ibero-American Conference on AI: Advances in Artificial Intelligence
An Interface Agent Approach to Personalize Users' Interaction with Databases
Journal of Intelligent Information Systems
Incremental learning of cognitive concepts: a hidden variable networks approach
PCAR '06 Proceedings of the 2006 international symposium on Practical cognitive agents and robots
HOTOS'05 Proceedings of the 10th conference on Hot Topics in Operating Systems - Volume 10
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Proceedings of the 2007 workshop on Service-oriented computing performance: aspects, issues, and approaches
Learning ontology for personalized video retrieval
Workshop on multimedia information retrieval on The many faces of multimedia semantics
Journal of Biomedical Informatics
Adapting Bayes network structures to non-stationary domains
International Journal of Approximate Reasoning
Automatic parameter tuning with a Bayesian case-based reasoning system. A case of study
Expert Systems with Applications: An International Journal
A Bayesian Approach to Attention Control and Concept Abstraction
Attention in Cognitive Systems. Theories and Systems from an Interdisciplinary Viewpoint
Adaptive Bayesian network classifiers
Intelligent Data Analysis
Performing incremental Bayesian inference by dynamic model counting
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Experimental evaluation of an automatic parameter setting system
Expert Systems with Applications: An International Journal
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Aggregating learned probabilistic beliefs
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Update rules for parameter estimation in Bayesian networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
iMMPC: a local search approach for incremental Bayesian network structure learning
IDA'11 Proceedings of the 10th international conference on Advances in intelligent data analysis X
Review: learning bayesian networks: Approaches and issues
The Knowledge Engineering Review
Confidence-Based incremental classification for objects with limited attributes in vertical search
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Efficiently adapting graphical models for selectivity estimation
The VLDB Journal — The International Journal on Very Large Data Bases
Financial Data Modeling using a Hybrid Bayesian Network Structured Learning Algorithm
International Journal of Cognitive Informatics and Natural Intelligence
Incremental causal network construction over event streams
Information Sciences: an International Journal
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There is an obvious need for improving the performance and accuracy of a Bayesian network as new data is observed. Because of errors in model construction and changes in the dynamics of the domains, we cannot afford to ignore the information in new data. While sequential update of parameters for a fixed structure can be accomplished using standard techniques, sequential update of network structure is still an open problem. In this paper, we investigate sequential update of Bayesian networks were both parameters and structure are expected to change. We introduce a new approach that allows for the flexible manipulation of the tradeoff between the quality of the learned networks and the amount of information that is maintained about past observations. We formally describe our approach including the necessary modifications to the scoring functions for learning Bayesian networks, evaluate its effectiveness through and empirical study, and extend it to the case of missing data.