Towards using the chordal graph polytope in learning decomposable models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F17%3A00475614" target="_blank" >RIV/67985556:_____/17:00475614 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.ijar.2017.06.001" target="_blank" >http://dx.doi.org/10.1016/j.ijar.2017.06.001</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ijar.2017.06.001" target="_blank" >10.1016/j.ijar.2017.06.001</a>
Alternative languages
Result language
angličtina
Original language name
Towards using the chordal graph polytope in learning decomposable models
Original language description
The motivation for this paper is the integer linear programming (ILP) approach to learning the structure of a decomposable graphical model. We have chosen to represent decomposable models by means of special zero-one vectors, named characteristic imsets. Our approach leads to the study of a special polytope, defined as the convex hull of all characteristic imsets for chordal graphs, named the chordal graph polytope. In this theoretical paper, we introduce a class of clutter inequalities (valid for the vectors in the polytope) and show that all of them are facet-defining for the polytope. We dare to conjecture that they lead to a complete polyhedral description of the polytope. Finally, we propose a linear programming method to solve the separation problem with these inequalities for the use in a cutting plane approach.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
<a href="/en/project/GA16-12010S" target="_blank" >GA16-12010S: Conditional independence structures: combinatorial and optimization methods</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Approximate Reasoning
ISSN
0888-613X
e-ISSN
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Volume of the periodical
88
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
23
Pages from-to
259-281
UT code for WoS article
000407655600014
EID of the result in the Scopus database
2-s2.0-85021109619