prindi

FARMUR: fair adversarial retraining to mitigate unfairness in robustness

autor
Mousavi, Seyed Ali
Mousavi, Hamid
Daneshtalab, Masoud
vastutusandmed
Seyed Ali Mousavi, Hamid Mousavi and Masoud Daneshtalab
allikas
Advances in Databases and Information Systems: 27th European Conference, ADBIS 2023, Barcelona, Spain, September 4–7, 2023 : proceedings
ilmumiskoht
Cham
kirjastus/väljaandja
Springer
ilmumisaasta
2023
leheküljed
p. 133-145
seeria-sari
Lecture notes in computer science ; 13985
konverentsi nimetus, aeg
27th European Conference on Advances in Databases and Information Systems , ADBIS 2023, 4-7 September 2023
konverentsi toimumispaik
Barcelona, Spain
leitav
https://doi.org/10.1007/978-3-031-42914-9_10
märksõna
tehisnärvivõrgud
õiglus
otsustamine
matemaatilised mudelid
Scopus
Conference proceedings at Scopus
Article at Scopus
kvartiil
Q3
kategooria (üld)
Computer science
Mathematics
kategooria (alam)
Computer science. General computer science
Mathematics. Theoretical computer science
võtmesõna
deep neural networks
fairness
fairness-in-robustness
robustness
robustness-bias
ISSN
0302-9743
ISBN
978-303142913-2
märkused
Lecture notes in computer science (Including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics)
Bibliogr.: 46 ref
teaduspublikatsioon
teaduspublikatsioon
klassifikaator
3.1
TTÜ struktuuriüksus
arvutisüsteemide instituut
keel
inglise
Mousavi, S.A., Mousavi, H., Daneshtalab, M. FARMUR: fair adversarial retraining to mitigate unfairness in robustness // Advances in Databases and Information Systems: 27th European Conference, ADBIS 2023, Barcelona, Spain, September 4–7, 2023 : proceedings. Cham : Springer, 2023. p. 133-145. (Lecture notes in computer science ; 13985). https://doi.org/10.1007/978-3-031-42914-9_10