Lifted Weight Learning of Markov Logic Networks Revisited
Proceedings of the Twenty-Second International Conference on Artificial Intelligence and Statistics, PMLR 89:1753-1761, 2019.
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.