publication . Conference object . Preprint . 2013

Credal Networks under Maximum Entropy

Thomas Lukasiewicz;
  • Published: 16 Jan 2013
  • Country: United Kingdom
Abstract
We apply the principle of maximum entropy to select a unique joint probability distribution from the set of all joint probability distributions specified by a credal network. In detail, we start by showing that the unique joint distribution of a Bayesian tree coincides with the maximum entropy model of its conditional distributions. This result, however, does not hold anymore for general Bayesian networks. We thus present a new kind of maximum entropy models, which are computed sequentially. We then show that for all general Bayesian networks, the sequential maximum entropy model coincides with the unique joint distribution. Moreover, we apply the new principle ...
Subjects
ACM Computing Classification System: TheoryofComputation_GENERAL
free text keywords: Computer Science - Artificial Intelligence
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