Elements of information theory
Elements of information theory
Learning and robust learning of product distributions
COLT '93 Proceedings of the sixth annual conference on Computational learning theory
A Linear-Time Algorithm for Finding Tree-Decompositions of Small Treewidth
SIAM Journal on Computing
Learning Markov networks: maximum bounded tree-width graphs
SODA '01 Proceedings of the twelfth annual ACM-SIAM symposium on Discrete algorithms
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
Learning bayesian networks from data
Learning bayesian networks from data
Learning with mixtures of trees
Learning with mixtures of trees
A practical algorithm for finding optimal triangulations
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Information geometry on hierarchy of probability distributions
IEEE Transactions on Information Theory
Proceedings of the 24th international conference on Machine learning
Efficient Heuristics for Discriminative Structure Learning of Bayesian Network Classifiers
The Journal of Machine Learning Research
Automatic model adaptation for complex structured domains
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
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We study the problem of projecting a distribution onto (or finding a maximum likelihood distribution among) Markov networks of bounded tree-width. By casting it as the combinatorial optimization problem of finding a maximum weight hypertree, we prove that it is NP-hard to solve exactly and provide an approximation algorithm with a provable performance guarantee.