Diffusion estimation of mixture models with local and global parameters
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F16%3A00461646" target="_blank" >RIV/67985556:_____/16:00461646 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/SSP.2016.7551775" target="_blank" >http://dx.doi.org/10.1109/SSP.2016.7551775</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SSP.2016.7551775" target="_blank" >10.1109/SSP.2016.7551775</a>
Alternative languages
Result language
angličtina
Original language name
Diffusion estimation of mixture models with local and global parameters
Original language description
The state-of-art methods for distributed estimation of mixtures assume the existence of a common mixture model. In many practical situations, this assumption may be too restrictive, as a subset of parameters may be purely local, e.g., if the numbers of observable components differ across the network. To reflect this issue, we propose a new online Bayesian method for simultaneous estimation of local parameters, and diffusion estimation of global parameters. The algorithm consists of two steps. First, the nodes perform local estimation from own observations by means of factorized prior/posterior distributions. Second, a diffusion optimization step is used to merge the nodes' global parameters estimates. A simulation example demonstrates improved performance in estimation of both parameters sets.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BD - Information theory
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
2016
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 2016 IEEE Workshop on Statistical Signal Processing
ISBN
978-1-4673-7802-4
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
362-366
Publisher name
IEEE
Place of publication
Palma de Mallorca, Španělsko
Event location
Palma de Mallorca
Event date
Jun 26, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000390840200071