Approximating Probabilistic Inference in Bayesian Belief Networks is NP-Hard.
Paul DagumMichael LubyPublished in: Artif. Intell. (1993)
Keyphrases
- bayesian belief networks
- probabilistic inference
- np hard
- belief networks
- conditional probabilities
- graphical models
- bayesian networks
- influence diagrams
- optimal solution
- special case
- approximate inference
- probabilistic networks
- probabilistic reasoning
- approximation algorithms
- message passing
- weighted model counting
- np complete
- lower bound
- exact inference
- neural network
- belief propagation
- data sets
- random variables
- conditional probability tables