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.
Cite
Text
Kuzelka and Kungurtsev. "Lifted Weight Learning of Markov Logic Networks Revisited." Artificial Intelligence and Statistics, 2019.Markdown
[Kuzelka and Kungurtsev. "Lifted Weight Learning of Markov Logic Networks Revisited." Artificial Intelligence and Statistics, 2019.](https://mlanthology.org/aistats/2019/kuzelka2019aistats-lifted/)BibTeX
@inproceedings{kuzelka2019aistats-lifted,
title = {{Lifted Weight Learning of Markov Logic Networks Revisited}},
author = {Kuzelka, Ondrej and Kungurtsev, Vyacheslav},
booktitle = {Artificial Intelligence and Statistics},
year = {2019},
pages = {1753-1761},
volume = {89},
url = {https://mlanthology.org/aistats/2019/kuzelka2019aistats-lifted/}
}