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1 Ergebnisse
1
MAFT: Efficient Model-Agnostic Fairness Testing for Deep Ne..:
, In:
2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE)
,
Wang, Zhaohui
;
Zhang, Min
;
Yang, Jingran
.. - p. 1484-1495 , 2024
Link:
https://doi.org/10.1145/3597503.3639181
RT T1 <cTitle>2024 IEEE/ACM 46th International Conference on Software Engineering (ICSE)</cTitle>: T1 <Title>MAFT: Efficient Model-Agnostic Fairness Testing for Deep Neural Networks via Zero-Order Gradient Search</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10548533&Exemplar=1&LAN=DE A1 Wang, Zhaohui A1 Zhang, Min A1 Yang, Jingran A1 Shao, Bojie A1 Zhang, Min YR 2024 SN 1558-1225 K1 Gradient methods K1 Perturbation methods K1 Closed box K1 Symbols K1 Computer architecture K1 Artificial neural networks K1 Rendering (computer graphics) K1 software bias K1 fairness testing K1 test case generation K1 deep neural network SP 1484 OP 1495 LK http://dx.doi.org/https://doi.org/10.1145/3597503.3639181 DO https://doi.org/10.1145/3597503.3639181 SF ELIB - SuUB Bremen
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