Dynamic Mixture Ratio Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F20%3A00524580" target="_blank" >RIV/67985556:_____/20:00524580 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICCAIRO47923.2019.00023" target="_blank" >http://dx.doi.org/10.1109/ICCAIRO47923.2019.00023</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCAIRO47923.2019.00023" target="_blank" >10.1109/ICCAIRO47923.2019.00023</a>
Alternative languages
Result language
angličtina
Original language name
Dynamic Mixture Ratio Model
Original language description
Finite mixtures of probability densities with components from exponential family serve as flexible parametric models of high-dimensional systems. However, with a few specialized exceptions, these dynamic models assume data-independent weights of mixture components. Their use is illogical and restricts the modeling applicability. The requirement for closeness with respect to conditioning, the basic learning operation, leads to a novel class of models: the mixture ratios. The paper justified them and shows their ability to model truly dynamic systems.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LTC18075" target="_blank" >LTC18075: Distributed rational decision making: cooperation aspects</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)
ISBN
978-1-7281-3573-1
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
92-99
Publisher name
IEEE
Place of publication
Piscataway
Event location
Athens
Event date
Dec 8, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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