Investigation of Gaussian Processes and Random Forests as Surrogate Models for Evolutionary Black-Box Optimization

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F15%3A00446913" target="_blank" >RIV/67985807:_____/15:00446913 - isvavai.cz</a>
Alternative codes found
RIV/00216208:11320/15:10334223
Result on the web
<a href="http://dx.doi.org/10.1145/2739482.2764692" target="_blank" >http://dx.doi.org/10.1145/2739482.2764692</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/2739482.2764692" target="_blank" >10.1145/2739482.2764692</a>

Result language
angličtina
Original language name
Investigation of Gaussian Processes and Random Forests as Surrogate Models for Evolutionary Black-Box Optimization
Original language description
This paper introduces two surrogate models for continous black-box optimization, Gaussian processes and random forests, as an alternative to the already used ordinal SVM regression. We employ the CMA-ES as the reference optimization method with which thesurrogate models are combined and also compared on subset of the noisless BBOB testing set.
Czech name
—
Czech description
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Project
<a href="/en/project/GA13-17187S" target="_blank" >GA13-17187S: Constructing Advanced Comprehensible Classifiers</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
GECCO Companion '15. Genetic and Evolutionary Computation Conference. Companion Material Proceedings
ISBN
978-1-4503-3488-4
ISSN
—
e-ISSN
—
Number of pages
2
Pages from-to
1351-1352
Publisher name
ACM
Place of publication
New York
Event location
Madrid
Event date
Jul 11, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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