Introduces entropy equivalence testing with a sample-efficient algorithm whose complexity is lower than standard closeness testing and applies it to improve closeness testing for low-degree Bayesian networks.
Near-Optimal Learning of Tree-Structured Distributions by Chow and Liu
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Entropy Equivalence Testing
Introduces entropy equivalence testing with a sample-efficient algorithm whose complexity is lower than standard closeness testing and applies it to improve closeness testing for low-degree Bayesian networks.