M. Studeny, D. Haws, R. Hemmecke, S. Lindner: Polyhedral approach to statistical learning graphical models. In Harmony of Groebner Bases and the Modern Industrial Society: the 2nd CREST--SBM International Conference (T. Hibi ed.), World Scientific, Singapore 2012, pages 346-372.

The statistical task to learn graphical models of Bayesian network structure from data leads to the study of special polyhedra. In the paper, we offer an overview of our polyhedral approach to learning these statistical models. First, we report on the results on this topic from our recent papers. The second part of the paper brings some specific additional results inspired by this approach.

AMS classification 68T30

Bayesian network structure
standard imset
characteristic imset
polyhedral geometry

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