Abstract
In [6], MCMC sampling is applied to approximately calculate the ratio of essential graphs (EGs) to directed acyclic graphs (DAGs) for up to 20 nodes. In the present paper, we extend that work from 20 to 31 nodes. We also extend that work by computing the approximate ratio of connected EGs to connected DAGs, of connected EGs to EGs, and of connected DAGs to DAGs. Furthermore, we prove that the latter ratio is asymptotically 1. We also discuss the implications of these results for learning DAGs from data.
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Peña, J.M. (2013). Approximate Counting of Graphical Models via MCMC Revisited. In: Bielza, C., et al. Advances in Artificial Intelligence. CAEPIA 2013. Lecture Notes in Computer Science(), vol 8109. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40643-0_39
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DOI: https://doi.org/10.1007/978-3-642-40643-0_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-40642-3
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