FARMUR: fair adversarial retraining to mitigate unfairness in robustness
author
Mousavi, Seyed Ali
Mousavi, Hamid
Daneshtalab, Masoud
statement of authorship
Seyed Ali Mousavi, Hamid Mousavi and Masoud Daneshtalab
source
Advances in Databases and Information Systems: 27th European Conference, ADBIS 2023, Barcelona, Spain, September 4–7, 2023 : proceedings
location of publication
Cham
publisher
Springer
year of publication
2023
pages
p. 133-145
series
Lecture notes in computer science ; 13985
conference name, date
27th European Conference on Advances in Databases and Information Systems , ADBIS 2023, 4-7 September 2023
conference location
Barcelona, Spain
url
https://doi.org/10.1007/978-3-031-42914-9_10
subject term
tehisnärvivõrgud
õiglus
otsustamine
matemaatilised mudelid
Scopus
https://www.scopus.com/sourceid/25674
https://www.scopus.com/record/display.uri?eid=2-s2.0-85190517138&origin=inward&txGid=d37dc9a1c5aa19f558a625f60a5071da
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
deep neural networks
fairness
fairness-in-robustness
robustness
robustness-bias
ISSN
0302-9743
ISBN
978-303142913-2
notes
Lecture notes in computer science (Including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics)
Bibliogr.: 46 ref
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
arvutisüsteemide instituut
language
inglise