Composite surrogate for likelihood-free bayesian optimisation in high-dimensional settings of activity-based transportation models
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
year of publication
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
ISSN
0302-9743
ISBN
78-3-030-74250-8
notes
Bibliogr.: 42 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
TTÜ department
language
inglise
subject term
keyword
Bayesian optimisation
high-dimensional data
likelihood-free inference
transportation model
kvartiil
classifier
category (general)
Kuzmanovski, V., Hollmén, J. Composite surrogate for likelihood-free bayesian optimisation in high-dimensional settings of activity-based transportation models // Advances in Intelligent Data Analysis XIX : 19th International Symposium on Intelligent Data Analysis, IDA 2021, Porto, Portugal, April 26–28, 2021 : proceedings. Cham : Springer Nature, 2021. p. 171-183 : ill. (Lecture notes in computer science ; 12695).