ML Anthology

Reading Dependencies from Polytree-like Bayesian Networks

José M. Peña
UAI 2007 pp. 303-309
/uai/2007/pena2007uai-reading/

Abstract

We present a graphical criterion for reading dependencies from the minimal directed independence map G of a graphoid p when G is a polytree and p satisfies composition and weak transitivity. We prove that the criterion is sound and complete. We argue that assuming composition and weak transitivity is not too restrictive.

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Cite

Text

Peña. "Reading Dependencies from Polytree-like Bayesian Networks." Conference on Uncertainty in Artificial Intelligence, 2007.

Markdown

[Peña. "Reading Dependencies from Polytree-like Bayesian Networks." Conference on Uncertainty in Artificial Intelligence, 2007.](https://mlanthology.org/uai/2007/pena2007uai-reading/)

BibTeX

@inproceedings{pena2007uai-reading,
  title     = {{Reading Dependencies from Polytree-like Bayesian Networks}},
  author    = {Peña, José M.},
  booktitle = {Conference on Uncertainty in Artificial Intelligence},
  year      = {2007},
  pages     = {303-309},
  url       = {https://mlanthology.org/uai/2007/pena2007uai-reading/}
}