On solution sets of information inequalities

Nihat Ay; Walter Wenzel

Kybernetika (2012)

  • Volume: 48, Issue: 5, page 845-864
  • ISSN: 0023-5954

Abstract

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We investigate solution sets of a special kind of linear inequality systems. In particular, we derive characterizations of these sets in terms of minimal solution sets. The studied inequalities emerge as information inequalities in the context of Bayesian networks. This allows to deduce structural properties of Bayesian networks, which is important within causal inference.

How to cite

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Ay, Nihat, and Wenzel, Walter. "On solution sets of information inequalities." Kybernetika 48.5 (2012): 845-864. <http://eudml.org/doc/251432>.

@article{Ay2012,
abstract = {We investigate solution sets of a special kind of linear inequality systems. In particular, we derive characterizations of these sets in terms of minimal solution sets. The studied inequalities emerge as information inequalities in the context of Bayesian networks. This allows to deduce structural properties of Bayesian networks, which is important within causal inference.},
author = {Ay, Nihat, Wenzel, Walter},
journal = {Kybernetika},
keywords = {linear inequalities; polyhedral sets; Bayesian networks; information; entropy; linear inequalities; polyhedral sets; Bayesian networks; information; entropy},
language = {eng},
number = {5},
pages = {845-864},
publisher = {Institute of Information Theory and Automation AS CR},
title = {On solution sets of information inequalities},
url = {http://eudml.org/doc/251432},
volume = {48},
year = {2012},
}

TY - JOUR
AU - Ay, Nihat
AU - Wenzel, Walter
TI - On solution sets of information inequalities
JO - Kybernetika
PY - 2012
PB - Institute of Information Theory and Automation AS CR
VL - 48
IS - 5
SP - 845
EP - 864
AB - We investigate solution sets of a special kind of linear inequality systems. In particular, we derive characterizations of these sets in terms of minimal solution sets. The studied inequalities emerge as information inequalities in the context of Bayesian networks. This allows to deduce structural properties of Bayesian networks, which is important within causal inference.
LA - eng
KW - linear inequalities; polyhedral sets; Bayesian networks; information; entropy; linear inequalities; polyhedral sets; Bayesian networks; information; entropy
UR - http://eudml.org/doc/251432
ER -

References

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  1. Ay, N., 10.1016/j.dam.2008.06.032, Discrete Appl. Math. 157 (2009), 2439-2457. MR2527961DOI10.1016/j.dam.2008.06.032
  2. Ay, N., Polani, D., 10.1142/S0219525908001465, Adv. Complex Systems 11 (2008), 1, 17-41. Zbl1163.94417MR2400125DOI10.1142/S0219525908001465
  3. Martini, H., Soltan, V., 10.1007/s000100050074, Aequationes Math. 57 (1999), 121-152. Zbl0937.52006MR1689190DOI10.1007/s000100050074
  4. Martini, H., Wenzel, W., Illumination and visibility problems in terms of closure operators., Beiträge zur Algebra und Geometrie 45 (2004), 2, 607-614. Zbl1074.52001MR2093030
  5. Pearl, J., Causality: Models, Reasoning and Inference., Cambridge University Press 2000. Zbl1188.68291MR1744773
  6. Steudel, B., Ay, N., Information-theoretic inference of common ancestors., Submitted. ArXiv preprint (2010) arXiv:1010.5720. 
  7. Valentine, F. A., 10.2307/2317326, Amer. Math. Monthly 77 (1970), 146-152. Zbl0189.52903MR0257881DOI10.2307/2317326
  8. Webster, R., Convexity., Oxford University Press 1994. Zbl1052.68785MR1443208
  9. Ziegler, G., Lectures on Polytopes., Springer Verlag Berlin 1997. Zbl0823.52002MR1311028

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