Structure and Parameter Learning for Causal Independence and Causal Interaction Models
Christopher MeekDavid HeckermanPublished in: CoRR (2013)
Keyphrases
- causal independence
- conditional independence
- bayesian networks
- structure and parameter learning
- belief networks
- probabilistic inference
- joint probability
- graphical models
- random variables
- probabilistic model
- probability distribution
- causal models
- parameter learning
- model selection
- conditional random fields
- markov logic networks
- prior knowledge
- maximum likelihood
- probabilistic reasoning
- machine learning