  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.
