Efficient algorithms for combinatorial problems on graphs with bounded, decomposability—a survey
BIT - Ellis Horwood series in artificial intelligence
Complexity of finding embeddings in a k-tree
SIAM Journal on Algebraic and Discrete Methods
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Bucket elimination: a unifying framework for probabilistic inference
Learning in graphical models
A sufficiently fast algorithm for finding close to optimal clique trees
Artificial Intelligence
Resolution versus Search: Two Strategies for SAT
Journal of Automated Reasoning
Likelihood Computations Using Value Abstraction
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
Pre-processing for Triangulation of Probabilistic Networks
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
A practical algorithm for finding optimal triangulations
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Topological parameters for time-space tradeoff
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
RC_Link: Genetic linkage analysis using Bayesian networks
International Journal of Approximate Reasoning
Approximate inference in probabilistic graphical models with determinism
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Cutset sampling for Bayesian networks
Journal of Artificial Intelligence Research
Join-graph propagation algorithms
Journal of Artificial Intelligence Research
SampleSearch: Importance sampling in presence of determinism
Artificial Intelligence
New advances in inference by recursive conditioning
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Importance sampling-based estimation over AND/OR search spaces for graphical models
Artificial Intelligence
Exploiting the probability of observation for efficient bayesian network inference
Canadian AI'12 Proceedings of the 25th Canadian conference on Advances in Artificial Intelligence
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Genetic linkage analysis is a challenging application which requires Bayesian networks consisting of thousands of vertices. Consequently, computing the likelihood of data, which is needed for learning linkage parameters, using exact inference procedures calls for an extremely efficient implementation that carefully optimizes the order of conditioning and summation operations. In this paper we present the use of stochastic greedy algorithms for optimizing this order. Our algorithm has been incorporated into the newest version of superlink, which is currently the fastest genetic linkage program for exact likelihood computations in general pedigrees. We demonstrate an order of magnitude improvement in run times of likelihood computations using our new optimization algorithm, and hence enlarge the class of problems that can be handled effectively by exact computations.