Improving Markov network structure learning using decision trees.
Daniel LowdJesse DavisPublished in: J. Mach. Learn. Res. (2014)
Keyphrases
- markov networks
- structure learning
- decision trees
- graphical models
- markov logic networks
- maximum likelihood
- first order logic
- belief propagation
- bayesian networks
- probabilistic graphical models
- parameter learning
- conditional independence tests
- bayesian inference
- probabilistic model
- conditional random fields
- posterior probability
- markov random field
- training data
- document classification
- conditional probabilities
- random variables
- hidden variables
- max margin
- machine learning
- inductive logic programming
- machine learning algorithms
- naive bayes
- training set
- maximum a posteriori
- missing data
- social networks
- learning algorithm