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Landes, Jürgen and Williamson, Jon (2016): Objective Bayesian Nets from Consistent Datasets. In: AIP Conference Proceedings, Vol. 1757, No. 1 [PDF, 304kB]

Abstract

This paper addresses the problem of finding a Bayesian net representation of the probability function that agrees with the distributions of multiple consistent datasets and otherwise has maximum entropy. We give a general algorithm which is significantly more efficient than the standard brute-force approach. Furthermore, we show that in a wide range of cases such a Bayesian net can be obtained without solving any optimisation problem.

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