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1
Measuring and Mitigating Unintended Bias in Text Classifica..:
, In:
Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society
,
Dixon, Lucas
;
Li, John
;
Sorensen, Jeffrey
.. - p. 67-73 , 2018
Link:
https://dl.acm.org/doi/10.1145/3278721.3278729
RT T1 <cTitle>Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society</cTitle>: T1 <Title>Measuring and Mitigating Unintended Bias in Text Classification</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3278729&Exemplar=1&LAN=DE A1 Dixon, Lucas A1 Li, John A1 Sorensen, Jeffrey A1 Thain, Nithum A1 Vasserman, Lucy PB ACM YR 2018 K1 algorithmic bias K1 fairness K1 machine learning K1 natural language processing K1 text classification K1 General and reference K1 Cross-computing tools and techniques K1 Measurement K1 Metrics K1 Evaluation K1 Computing methodologies K1 Artificial intelligence K1 Natural language processing K1 Machine learning K1 Discourse, dialogue and pragmatics K1 Learning paradigms K1 Supervised learning K1 Supervised learning by classification K1 Machine learning approaches K1 Neural networks SP 67 OP 73 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3278721.3278729 DO https://dl.acm.org/doi/10.1145/3278721.3278729 SF ELIB - SuUB Bremen
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