Comparison of ordinal and metric gaussian process regression as surrogate models for CMA evolution strategy
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023752%3A_____%2F17%3A43918929" target="_blank" >RIV/00023752:_____/17:43918929 - isvavai.cz</a>
Alternative codes found
RIV/67985807:_____/17:00477789
Result on the web
<a href="https://dl.acm.org/citation.cfm?doid=3067695.3084206" target="_blank" >https://dl.acm.org/citation.cfm?doid=3067695.3084206</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3067695.3084206" target="_blank" >10.1145/3067695.3084206</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of ordinal and metric gaussian process regression as surrogate models for CMA evolution strategy
Original language description
In this paper, Gaussian processes are studied in connection with the state-of-the-art method for continuous black-box optimization CMA-ES. To combine them with the CMA-ES is challenging because CMA-ES invariance with respect to order preserving transformations suggests ordinal regression, whereas Gaussian process continuity suggests metric regression. Results of testing ordinal and metric Gaussian process regression, the former in 14 dierent seings, combined with the CMA-ES on noiseless benchmarks of the COCO platform are reported.
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
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017; Berlin; Germany; 15 July 2017 through 19 July 2017
ISBN
978-1-4503-4939-0
ISSN
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e-ISSN
neuvedeno
Number of pages
8
Pages from-to
1764-1771
Publisher name
ACM
Place of publication
New York
Event location
Berlin, Germany
Event date
Jul 15, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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