A Permutation-Based Kernel Conditional Independence Test.
Gary DoranKrikamol MuandetKun ZhangBernhard SchölkopfPublished in: UAI (2014)
Keyphrases
- conditional independence
- bayesian networks
- random variables
- graphical models
- structure learning
- learning bayesian networks
- directed acyclic graph
- probability distribution
- statistical independence
- causal models
- axiomatic characterization
- possibility theory
- bayesian network structure
- gaussian model
- kernel function
- structure and parameter learning
- probability theory
- causal independence
- markov property
- support vector
- chain graphs
- missing data