Number of the records: 1
Polyhedral approach to statistical learning graphical models
- 1.0377257 - ÚTIA 2013 RIV SG eng C - Conference Paper (international conference)
Studený, Milan - Haws, D. - Hemmecke, R. - Lindner, S.
Polyhedral approach to statistical learning graphical models.
Harmony of Gröbner Bases and the Modern Industrial Society. Singapore: World Scientific Press, 2012, s. 346-372. ISBN 978-981-4383-45-5.
[The 2nd CREST-SBM International Conference "Harmony of Groebner Bases and the Modern Industrial Society". Osaka (JP), 28.06.2012-2.07.2012]
R&D Projects: GA ČR GA201/08/0539
Institutional support: RVO:67985556
Keywords : Bayesian network stucture * standard imset * characteristic imset * polyhedral geometry
Subject RIV: BA - General Mathematics
http://library.utia.cas.cz/separaty/2012/MTR/studeny-polyhedral approach to statistical learning graphical models.pdf
The statistical task to learn graphical models of Bayesian network structure 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.
Permanent Link: http://hdl.handle.net/11104/0209464
Number of the records: 1