A recurrence local computation approach towards ordering composite beliefs in bayesian belief networks

@article{Sy1993ARL,
  title={A recurrence local computation approach towards ordering composite beliefs in bayesian belief networks},
  author={Bon K. Sy},
  journal={Int. J. Approx. Reasoning},
  year={1993},
  volume={8},
  pages={17-50}
}
Finding the l Most Probable Explanations (MPE) of a given evidence, S e , in a Bayesian belief network can be formulated as identifying and ordering a set of composite hypotheses, H i s, of which the posterior probabilities are the l largest; i.e., Pr(H 1 jS e) ::: Pr(H l jS e). When an order includes all the composite hypotheses in the network in order to nd all the probable explanations, it becomes a total order and the derivation of such an order has an exponential complexity. The focus of… CONTINUE READING

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