Operations Research
Probabilistic inference and influence diagrams
Operations Research
Approximating probabilistic inference in Bayesian belief networks is NP-hard
Artificial Intelligence
LAZY propagation: a junction tree inference algorithm based on lazy evaluation
Artificial Intelligence
Probabilistic Networks and Expert Systems
Probabilistic Networks and Expert Systems
Local Propagation in Conditional Gaussian Bayesian Networks
The Journal of Machine Learning Research
Exploiting causal independence in Bayesian network inference
Journal of Artificial Intelligence Research
Query DAGs: a practical paradigm for implementing belief-network inference
Journal of Artificial Intelligence Research
Any-space probabilistic inference
UAI'00 Proceedings of the Sixteenth 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
Topological parameters for time-space tradeoff
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Value elimination: bayesian inference via backtracking search
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
An improved LAZY-AR approach to bayesian network inference
AI'06 Proceedings of the 19th international conference on Advances in Artificial Intelligence: Canadian Society for Computational Studies of Intelligence
Variations over the message computation algorithm of lazy propagation
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Approximate inference in Bayesian networks using binary probability trees
International Journal of Approximate Reasoning
Join tree propagation utilizing both arc reversal and variable elimination
International Journal of Approximate Reasoning
Using four cost measures to determine arc reversal orderings
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Evaluating probabilistic inference techniques: a question of "When," not "Which"
SUM'11 Proceedings of the 5th international conference on Scalable uncertainty management
A search problem in complex diagnostic Bayesian networks
Knowledge-Based Systems
Answering queries in hybrid Bayesian networks using importance sampling
Decision Support Systems
Ordering arc-reversal operations when eliminating variables in lazy AR propagation
International Journal of Approximate Reasoning
On the tree structure used by lazy propagation for inference in bayesian networks
ECSQARU'13 Proceedings of the 12th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
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Even though existing algorithms for belief update in Bayesian networks (BNs) have exponential time and space complexity, belief update in many real-world BNs is feasible. However, in some cases the efficiency of belief update may be insufficient. In such cases minor improvements in efficiency may be important or even necessary to make a task tractable. This paper introduces two improvements to the message computation in Lazy propagation (LP): (1) we introduce myopic methods for sorting the operations involved in a variable elimination using arc-reversal and (2) extend LP with the any-space property. The performance impacts of the methods are assessed empirically.