Decomposing Local Probability Distributions in Bayesian Networks for Improved Inference and Parameter Learning.
Adam ZagoreckiMark VoortmanMarek J. DruzdzelPublished in: FLAIRS Conference (2006)
Keyphrases
- parameter learning
- bayesian networks
- probability distribution
- structure learning
- random variables
- bayesian network learning
- conditional probabilities
- probabilistic model
- probabilistic modeling
- factor graphs
- conditional independence
- posterior probability
- probabilistic inference
- graphical models
- probabilistic graphical models
- hidden variables
- maximum likelihood
- posterior distribution
- em algorithm
- exact inference
- statistical learning
- belief networks
- conditional random fields
- maximum likelihood estimation
- bayesian network classifiers
- decision trees
- expectation maximization
- parameter estimation
- approximate inference
- machine learning