Learning Efficient Markov Networks

  title={Learning Efficient Markov Networks},
  author={Vibhav Gogate and William Austin Webb and Pedro M. Domingos},
We present an algorithm for learning high-treewidth Markov networks where inference is still tractable. This is made possible by exploiting context-specific independence and determinism in the domain. The class of models our algorithm can learn has the same desirable properties as thin junction trees: polynomial inference, closed-form weight learning, etc., but is much broader. Our algorithm searches for a feature that divides the state space into subspaces where the remaining variables… CONTINUE READING

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