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
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Local and global relational consistency
Theoretical Computer Science - Special issue: principles and practice of constraint programming
Mini-buckets: a general scheme for generating approximations in automated reasoning
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Bucket elimination: a unifying framework for probabilistic inference
UAI'96 Proceedings of the Twelfth international conference on Uncertainty in artificial intelligence
Simulation-based inference for plan monitoring
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
ACM Computing Surveys (CSUR)
Mini-buckets: A general scheme for bounded inference
Journal of the ACM (JACM)
New Search Heuristics for Max-CSP
CP '02 Proceedings of the 6th International Conference on Principles and Practice of Constraint Programming
A General Scheme for Multiple Lower Bound Computation in Constraint Optimization
CP '01 Proceedings of the 7th International Conference on Principles and Practice of Constraint Programming
Generating random solutions for constraint satisfaction problems
Eighteenth national conference on Artificial intelligence
Tree approximation for belief updating
Eighteenth national conference on Artificial intelligence
Accuracy vs. efficiency trade-offs in probabilistic diagnosis
Eighteenth national conference on Artificial intelligence
Probabilistic fault localization in communication systems using belief networks
IEEE/ACM Transactions on Networking (TON)
Collaborative Multiagent Reinforcement Learning by Payoff Propagation
The Journal of Machine Learning Research
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
Branch and bound with mini-bucket heuristics
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
International Journal of Approximate Reasoning
Join-graph propagation algorithms
Journal of Artificial Intelligence Research
Multi-dimensional classification with Bayesian networks
International Journal of Approximate Reasoning
Communication-constrained DCOPs: message approximation in GDL with function filtering
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Mini-bucket heuristics for improved search
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Iterative join-graph propagation
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Tractable inference for complex stochastic processes
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
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Systematic vs. non-systematic algorithms for solving the MPE task
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Semiring-based mini-bucket partitioning schemes
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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This paper describes a class of probabilistic approximation algorithms based on bucket elimination which offer adjustable levels of accuracy and efficiency. We analyze the approximation for several tasks: finding the most probable explanation, belief updating and finding the maximum a posteriori hypothesis. We identify regions of completeness and provide preliminary empirical evaluation on randomly generated networks.