Adaptive importance sampling for Bayesian inference in Gaussian process models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23220%2F14%3A43922643" target="_blank" >RIV/49777513:23220/14:43922643 - isvavai.cz</a>
Result on the web
<a href="http://10.3182/20140824-6-ZA-1003.02352" target="_blank" >http://10.3182/20140824-6-ZA-1003.02352</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3182/20140824-6-ZA-1003.02352" target="_blank" >10.3182/20140824-6-ZA-1003.02352</a>
Alternative languages
Result language
angličtina
Original language name
Adaptive importance sampling for Bayesian inference in Gaussian process models
Original language description
Gaussian process (GP) models are nowadays considered among the standard tools in modern control system engineering. They are routinely used for model-based control, time- series prediction, modelling and estimation in engineering applications. While theunderlying theory is completely in line with the principles of Bayesian inference, in practice this property is lost due to approximation steps in the GP inference. In this paper we propose a novel inference algorithm for GP models, which relies on adaptive importance sampling strategy to numerically evaluate the intractable marginalization over the hyperparameters. This is required in the case of broad-peaked or multi-modal posterior distribution of the hyperparameters where the point approximations turn out to be insufficient. The benefits of the algorithm are that is retains the Bayesian nature of the inference, has sufficient convergence properties, relatively low computational load and does not require heavy prior knowledge due to
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JA - Electronics and optoelectronics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/ED2.1.00%2F03.0094" target="_blank" >ED2.1.00/03.0094: Regional Innovation Centre for Electrical Engineering (RICE)</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
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
Proceedings of the 19th IFAC World Congress, 2014
ISBN
978-3-902823-62-5
ISSN
1474-6670
e-ISSN
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Number of pages
6
Pages from-to
5011-5016
Publisher name
Elsevier
Place of publication
Amsterdam
Event location
Cape Town
Event date
Aug 24, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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