A Novel Approach to Handle Inference in Discrete Markov Networks with Large Label Sets.
Alexander Oliver MaderJens von BergCristian LorenzCarsten MeyerPublished in: PGM (2018)
Keyphrases
- markov networks
- markov logic
- structured prediction
- bayesian inference
- graphical models
- markov logic networks
- collective classification
- bayesian networks
- pseudo likelihood
- probabilistic graphical models
- maximum likelihood
- probabilistic inference
- statistical relational learning
- belief propagation
- exact inference
- maximum margin
- entity resolution
- first order logic
- probabilistic model
- hidden variables
- conditional random fields
- relational dependency networks
- structure learning
- document classification
- bayes nets
- markov random field
- probabilistic reasoning
- random fields
- conditional probabilities
- maximum a posteriori
- approximate inference
- posterior probability
- graph cuts
- special case
- hidden markov models
- relational data
- knn
- particle filter
- parameter learning
- belief networks
- em algorithm
- knowledge base
- generative model