Making Pairwise Binary Graphical Models Attractive.
Nicholas RuozziTony JebaraPublished in: NIPS (2014)
Keyphrases
- graphical models
- belief propagation
- pairwise
- probabilistic model
- random variables
- approximate inference
- probabilistic graphical models
- conditional random fields
- probabilistic inference
- message passing
- bayesian networks
- map inference
- markov networks
- structure learning
- similarity measure
- graph structure
- statistical inference
- conditional independence
- factor graphs
- higher order
- statistical relational learning
- loopy belief propagation
- exact inference
- hidden markov models
- lower bound
- multi class
- loss function
- gaussian graphical models
- directed graphical models