Traditional Gaussian Process Surrogates in the BBOB Framework
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F16%3A00462909" target="_blank" >RIV/67985807:_____/16:00462909 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/16:10334234
Result on the web
<a href="http://ceur-ws.org/Vol-1649/163.pdf" target="_blank" >http://ceur-ws.org/Vol-1649/163.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Traditional Gaussian Process Surrogates in the BBOB Framework
Original language description
Objective function evaluation in continuous optimization tasks is often the operation that dominates the algorithm’s cost. In particular in the case of black-box functions, i.e. when no analytical description is available, and the function is evaluated empirically. In such a situation, utilizing information from a surrogate model of the objective function is a well known technique to accelerate the search. In this paper, we review two traditional approaches to surrogate modelling based on Gaussian processes that we have newly reimplemented in MATLAB: Metamodel Assisted Evolution Strategy using probability of improvement and Gaussian Process Optimization Procedure. In the research reported in this paper, both approaches have been for the first time evaluated on Black-Box Optimization Benchmarking framework (BBOB), a comprehensive benchmark for continuous optimizers.
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
<a href="/en/project/NV15-33250A" target="_blank" >NV15-33250A: Prediction of therapeutic response in patients with depressive disorder by means of new methods of EEG analysis.</a><br>
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 ITAT 2016: Information Technologies - Applications and Theory
ISBN
978-1-5370-1674-0
ISSN
1613-0073
e-ISSN
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Number of pages
9
Pages from-to
163-171
Publisher name
Technical University & CreateSpace Independent Publishing Platform
Place of publication
Aachen & Charleston
Event location
Tatranské Matliare
Event date
Sep 15, 2016
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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