Approximating Probability Densities by Mixtures of Gaussian Dependence Trees
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F14%3A00435901" target="_blank" >RIV/67985556:_____/14:00435901 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Approximating Probability Densities by Mixtures of Gaussian Dependence Trees
Original language description
Considering the probabilistic approach to practical problems we are increasingly confronted with the need to estimate unknown multivariate probability density functions from large high-dimensional databases produced by electronic devices. The underlyingdensities are usually strongly multimodal and therefore mixtures of unimodal density functions suggest themselves as a suitable approximation tool. In this respect the product mixture models are preferable because they can be efficiently estimated from data by means of EM algorithm and have some advantageous properties. However, in some cases the simplicity of product components could appear too restrictive and a natural idea is to use a more complex mixture of dependence-tree densities. The dependencetree densities can explicitly describe the statistical relationships between pairs of variables at the level of individual components and therefore the approximation power of the resulting mixture may essentially increase.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Stochastic and Physical Monitoring Systems, SPMS 2014
ISBN
978-80-01-05616-5
ISSN
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e-ISSN
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Number of pages
13
Pages from-to
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Publisher name
ČVUT
Place of publication
Praha
Event location
Malá Skála
Event date
Jun 23, 2014
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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