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Bounded Conditioning: Flexible Inference for Decisions under Scarce Resources
We introduce a graceful approach to probabilistic inference called bounded conditioning.
Updating Probabilities in Multiply-Connected Belief Networks
This paper focuses on probability updates in multiply-connected belief networks.
A Combination of Cutset Conditioning with Clique-Tree Propagation in the Pathfinder System
Cutset conditioning and clique-tree propagation are two popular methods for performing exact probabilistic inference in Bayesian belief networks.
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