Lifted Weight Learning of Markov Logic Networks Revisited

Ondrej Kuzelka; Vyacheslav Kungurtsev

AISTATS 2019poster8 citations

Lifted Weight Learning of Markov Logic Networks Revisited

Abstract

We study lifted weight learning of Markov logic networks. We show that there is an algorithm for maximum-likelihood learning of 2-variable Markov logic networks which runs in time polynomial in the domain size. Our results are based on existing lifted-inference algorithms and recent algorithmic results on computing maximum entropy distributions.

BibTeX

@InProceedings{pmlr-v89-kuzelka19a,
  title = 	 {Lifted Weight Learning of Markov Logic Networks Revisited},
  author =       {Kuzelka, Ondrej and Kungurtsev, Vyacheslav},
  booktitle = 	 {Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics},
  pages = 	 {1753--1761},
  year = 	 {2019},
  editor = 	 {Chaudhuri, Kamalika and Sugiyama, Masashi},
  volume = 	 {89},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {16--18 Apr},
  publisher =    {PMLR},
  pdf = 	 {http://proceedings.mlr.press/v89/kuzelka19a/kuzelka19a.pdf},
  url = 	 {https://proceedings.mlr.press/v89/kuzelka19a.html},
  abstract = 	 {We study lifted weight learning of Markov logic networks. We show that there is an algorithm for maximum-likelihood learning of 2-variable Markov logic networks which runs in time polynomial in the domain size. Our results are based on existing lifted-inference algorithms and recent algorithmic results on computing maximum entropy distributions.}
}