Composite surrogate for likelihood-free bayesian optimisation in high-dimensional settings of activity-based transportation models
author
Kuzmanovski, Vladimir
Hollmén, Jaakko
statement of authorship
Vladimir Kuzmanovski and Jaakko Hollmén
source
Advances in Intelligent Data Analysis XIX : 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26–28, 2021 : proceedings
location of publication
Cham
publisher
Springer Nature
year of publication
2021
pages
p. 171-183 : ill
series
Lecture notes in computer science ; 12695
conference name, date
19th International Symposium on Intelligent Data Analysis, IDA 2021, April 26–28, 2021
conference location
Porto, Portugal
url
https://doi.org/10.1007/978-3-030-74251-5_14
subject term
kõrgdimensionaalsed andmed
kalibreerimine
normaaljaotus
mudelid
Scopus
https://www.scopus.com/sourceid/25674
https://www.scopus.com/record/display.uri?eid=2-s2.0-85105887493&origin=inward&txGid=b766e0b39ee6feeb6dd1de80e9bf5505
WOS
https://jcr.clarivate.com/jcr-jp/journal-profile?journal=LECT%20NOTES%20ARTIF%20INT&year=2005
https://www.webofscience.com/wos/woscc/full-record/WOS:000722625800014
quartile
Q3
category (general)
Computer science
Arvutiteadus
Mathematics
Matemaatika
category (sub)
Computer science. General computer science
Arvutiteadus. Üldine arvutiteadus
Mathematics. Theoretical computer science
Matemaatika. Teoreetiline arvutiteadus
keyword
Bayesian optimisation
high-dimensional data
likelihood-free inference
random forest
transportation model
ISSN
0302-9743
ISBN
78-3-030-74250-8
notes
Bibliogr.: 42 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
Targa linna tippkeskus
language
inglise