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
subject term
kõrgdimensionaalsed andmed
kvartiil
Q3
category (general)
keyword
Bayesian optimisation
high-dimensional data
likelihood-free inference
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
TTÜ department
language
inglise
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). https://doi.org/10.1007/978-3-030-74251-5_14