täiskirje prindi

Evaluating the robustness of ML models to out-of-distribution data through similarity analysis

autor
Lindén, Joakim
Forsberg, Håkan
Daneshtalab, Masoud
Söderquist, Ingemar
vastutusandmed
Joakim Lindén, Håkan Forsberg, Masoud Daneshtalab & Ingemar Söderquist
allikas
New Trends in Database and Information Systems; ADBIS 2023 Short Papers, Doctoral Consortium and Workshops: AIDMA, DOING, K-Gals, MADEISD, PeRS, Barcelona, Spain, September 4–7, 2023, Proceedings
ilmumiskoht
Cham
kirjastus/väljaandja
ilmumisaasta
leheküljed
p. 348 - 359
seeria-sari
konverentsi nimetus, aeg
27th European Conference on Advances in Databases and Information Systems, ADBIS 2023, 4-7 September 2023
konverentsi toimumispaik
Barcelona, Spain
leitav
ISSN
1865-0929
ISBN
978-303142940-8
märkused
Bibliogr.: 20 ref
teaduspublikatsioon
teaduspublikatsioon
TTÜ struktuuriüksus
keel
inglise
märksõna
võtmesõna
accuracy estimation
datasets
neural networks
similarity metrics
Lindén, J., Forsberg, H., Daneshtalab, M., Söderquist, I. Evaluating the robustness of ML models to out-of-distribution data through similarity analysis // New Trends in Database and Information Systems; ADBIS 2023 Short Papers, Doctoral Consortium and Workshops: AIDMA, DOING, K-Gals, MADEISD, PeRS, Barcelona, Spain, September 4–7, 2023, Proceedings. Cham : Springer Nature, 2023. p. 348 - 359. (Communications in computer and information science ; 1850). https://doi.org/10.1007/978-3-031-42941-5_30