The IBMAP approach for Markov network structure learning.
Federico SchlüterFacundo BrombergAlejandro EderaPublished in: Ann. Math. Artif. Intell. (2014)
Keyphrases
- markov networks
- structure learning
- graphical models
- maximum likelihood
- bayesian networks
- belief propagation
- first order logic
- probabilistic graphical models
- markov logic networks
- bayesian inference
- probabilistic model
- conditional random fields
- parameter learning
- markov random field
- inductive logic programming
- posterior probability
- document classification
- hidden variables
- max margin
- conditional probabilities
- random variables
- pairwise
- expert systems
- decision trees
- probability distribution