Tractable Learning of Liftable Markov Logic Networks

@inproceedings{VANHAAREN2014TractableLO,
  title={Tractable Learning of Liftable Markov Logic Networks},
  author={JAN. VANHAAREN and BE CS.KULEUVEN. and GUY. VANDENBROECK and WANNES. MEERT and JESSE. DAVIS},
  year={2014}
}
  • JAN. VANHAAREN, BE CS.KULEUVEN., +2 authors JESSE. DAVIS
  • Published 2014
Markov logic networks (MLNs) are a popular statistical relational learning formalism that combine Markov networks with first-order logic. Unfortunately, inference and maximum-likelihood learning with MLNs is highly intractable. For inference, this problem is addressed by lifted algorithms, which speed up inference by exploiting symmetries. State-of-the-art lifted algorithms give tractability guarantees for broad classes of MLNs and inference tasks. For learning, we showed in recent work how to… CONTINUE READING
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