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1
Fairness-Aware Machine Learning : Practical Challenges a..:
, In:
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining
,
Bird, Sarah
;
Kenthapadi, Krishnaram
;
Kiciman, Emre
. - p. 834-835 , 2019
Link:
https://dl.acm.org/doi/10.1145/3289600.3291383
RT T1
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining
: T1
Fairness-Aware Machine Learning : Practical Challenges and Lessons Learned
UL https://suche.suub.uni-bremen.de/peid=acm-3291383&Exemplar=1&LAN=DE A1 Bird, Sarah A1 Kenthapadi, Krishnaram A1 Kiciman, Emre A1 Mitchell, Margaret PB ACM YR 2019 K1 algorithmic bias K1 fairness case studies from industry K1 fairness definitions K1 fairness-aware machine learning K1 legal frameworks on bias and discrimination K1 sources of bias K1 Social and professional topics K1 Professional topics K1 Computing and business K1 Socio-technical systems K1 Computing methodologies K1 Artificial intelligence K1 Security and privacy K1 Human and societal aspects of security and privacy SP 834 OP 835 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3289600.3291383 DO https://dl.acm.org/doi/10.1145/3289600.3291383 SF ELIB - SuUB Bremen
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