Lifted Weight Learning of Markov Logic Networks Revisited

Ondrej Kuzelka, Vyacheslav Kungurtsev
Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, PMLR 89:1753-1761, 2019.

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 this Paper

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.} }
Endnote
%0 Conference Paper %T Lifted Weight Learning of Markov Logic Networks Revisited %A Ondrej Kuzelka %A Vyacheslav Kungurtsev %B Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics %C Proceedings of Machine Learning Research %D 2019 %E Kamalika Chaudhuri %E Masashi Sugiyama %F pmlr-v89-kuzelka19a %I PMLR %P 1753--1761 %U https://proceedings.mlr.press/v89/kuzelka19a.html %V 89 %X 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.
APA
Kuzelka, O. & Kungurtsev, V.. (2019). Lifted Weight Learning of Markov Logic Networks Revisited. Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, in Proceedings of Machine Learning Research 89:1753-1761 Available from https://proceedings.mlr.press/v89/kuzelka19a.html.

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