Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Connectionist learning of belief networks
Artificial Intelligence
Approximating probabilistic inference in Bayesian belief networks is NP-hard
Artificial Intelligence
Structuring conditional relationships in influence diagrams
Operations Research
Probabilistic Horn abduction and Bayesian networks
Artificial Intelligence
Knowledge representation and inference in similarity networks and Bayesian multinets
Artificial Intelligence
Local conditioning in Bayesian networks
Artificial Intelligence
Abstraction and approximate decision-theoretic planning
Artificial Intelligence
Nonserial Dynamic Programming
On the Role of Context-Specific Independence in Probabilistic Inference
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Context-specific multiagent coordination and planning with factored MDPs
Eighteenth national conference on Artificial intelligence
Probabilistic partial evaluation: exploiting rule structure in probabilistic inference
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Mean field theory for sigmoid belief networks
Journal of Artificial Intelligence Research
Exploiting causal independence in Bayesian network inference
Journal of Artificial Intelligence Research
Exploiting structure in policy construction
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Context-specific approximation in probabilistic inference
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Conditioning algorithms for exact and approximate inference in causal networks
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Exploiting the rule structure for decision making within the independent choice logic
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Correlated action effects in decision theoretic regression
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
A Bayesian approach to learning Bayesian networks with local structure
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
A sufficiently fast algorithm for finding close to optimal junction trees
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Context-specific independence in Bayesian networks
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Bucket elimination: a unifying framework for probabilistic inference
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Learning Bayesian networks with local structure
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Interestingness of frequent itemsets using Bayesian networks as background knowledge
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
ACM Transactions on Computational Logic (TOCL)
Conditional independence and chain event graphs
Artificial Intelligence
On probabilistic inference by weighted model counting
Artificial Intelligence
Explaining inferences in Bayesian networks
Applied Intelligence
On Directed and Undirected Propagation Algorithms for Bayesian Networks
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Finding Minimum Data Requirements Using Pseudo-independence
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
Performing Bayesian inference by weighted model counting
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Compiling Bayesian networks using variable elimination
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
First-order probabilistic inference
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Compiling Bayesian networks with local structure
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Optimizing inference in Bayesian networks and semiring valuation algebras
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
The independent choice logic and beyond
Probabilistic inductive logic programming
Temporal action-graph games: a new representation for dynamic games
UAI '09 Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence
Causal analysis with Chain Event Graphs
Artificial Intelligence
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
ILP'09 Proceedings of the 19th international conference on Inductive logic programming
Bayesian MAP model selection of chain event graphs
Journal of Multivariate Analysis
LPNMR'11 Proceedings of the 11th international conference on Logic programming and nonmonotonic reasoning
Review: learning bayesian networks: Approaches and issues
The Knowledge Engineering Review
A search problem in complex diagnostic Bayesian networks
Knowledge-Based Systems
Learning Ground CP-Logic Theories by Leveraging Bayesian Network Learning Techniques
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
Causal identifiability via Chain Event Graphs
Artificial Intelligence
Refining a Bayesian Network using a Chain Event Graph
International Journal of Approximate Reasoning
Probabilistic reasoning with undefined properties in ontologically-based belief networks
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Bayesian belief networks have grown to prominence because they provide compact representations for many problems for which probabilistic inference is appropriate, and there are algorithms to exploit this compactness. The next step is to allow compact representations of the conditional probabilities of a variable given its parents. In this paper we present such a representation that exploits contextual independence in terms of parent contexts; which variables act as parents may depend on the value of other variables. The internal representation is in terms of contextual factors (confactors) that is simply a pair of a context and a table. The algorithm, contextual variable elimination, is based on the standard variable elimination algorithm that eliminates the nonquery variables in turn, but when eliminating a variable, the tables that need to be multiplied can depend on the context. This algorithm reduces to standard variable elimination when there is no contextual independence structure to exploit. We show how this can be much more efficient than variable elimination when there is structure to exploit. We explain why this new method can exploit more structure than previous methods for structured belief network inference and an analogous algorithm that uses trees.