Heuristics: intelligent search strategies for computer problem solving
Heuristics: intelligent search strategies for computer problem solving
Efficient algorithms for combinatorial problems on graphs with bounded, decomposability—a survey
BIT - Ellis Horwood series in artificial intelligence
Network-based heuristics for constraint-satisfaction problems
Artificial Intelligence
Valuation-based systems for Bayesian decision analysis
Operations Research
On Fourier's algorithm for linear arithmetic constraints
Journal of Automated Reasoning
Graph minors. XIII: the disjoint paths problem
Journal of Combinatorial Theory Series B
A Computing Procedure for Quantification Theory
Journal of the ACM (JACM)
Local and Global Relational Consistency
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
Exploiting causal independence in Bayesian network inference
Journal of Artificial Intelligence Research
Bucket elimination: a unifying framework for probabilistic inference
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Mini-buckets: A general scheme for bounded inference
Journal of the ACM (JACM)
Arc consistency for soft constraints
Artificial Intelligence
Semiring induced valuation algebras: Exact and approximate local computation algorithms
Artificial Intelligence
Multivariate analysis applied in Bayesian metareasoning
WSEAS TRANSACTIONS on SYSTEMS
Adaptive traitor tracing with Bayesian networks
IAAI'07 Proceedings of the 19th national conference on Innovative applications of artificial intelligence - Volume 2
Variational probabilistic inference and the QMR-DT network
Journal of Artificial Intelligence Research
Solving weighted constraint satisfaction problems with memetic/exact hybrid algorithms
Journal of Artificial Intelligence Research
Exploiting decomposition on constraint problems with high tree-width
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Structural relaxations by variable renaming and their compilation for solving MinCostSAT
CP'07 Proceedings of the 13th international conference on Principles and practice of constraint programming
Multiattribute auctions based on generalized additive independence
Journal of Artificial Intelligence Research
Recursive probability trees for Bayesian networks
CAEPIA'09 Proceedings of the Current topics in artificial intelligence, and 13th conference on Spanish association for artificial intelligence
UCP-networks: a directed graphical representation of conditional utilities
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
The factored frontier algorithm for approximate inference in DBNs
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Using qualitative relationships for bounding probability distributions
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Context-specific approximation in probabilistic inference
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Empirical evaluation of approximation algorithms for probabilistic decoding
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A scheme for approximating probabilistic inference
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
A multi-level memetic/exact hybrid algorithm for the still life problem
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Duality in optimization and constraint satisfaction
CPAIOR'06 Proceedings of the Third international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
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The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustable levels of accuracy and efficiency, and they can be applied uniformly across many areas and problem tasks. We introduce these algorithms in the context of combinatorial optimization and probabilistic inference.