Dynamic Fairness
Dynamic Fairness is a fairness metric in machine learning that, as a temporal adaptation of static fairness criteria, accounts for evolving relationships between sensitive attributes and outcomes over time to ensure equitable model behavior across sequential decision-making contexts.
7
Publications
126
Citations
18
Authors
11
Institutions
Publications per year
2017–2026
4
Parents
7
Process fairness and dynamic consistency
Stefan T. Trautmann, Peter P. Wakker · Economics Letters · 2010 · 33 citations · Full text
Runtime Monitoring of Dynamic Fairness Properties
Thomas A. Henzinger, Mahyar Karimi, Konstantin Kueffner et al. · 2023 · 17 citations · Full text
1–5 of 7
18
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Bangladesh University of Engineering and Technology, Bangladesh
1 publications · 17 citations
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1
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1
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1
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1–5 of 18
11
Erasmus University Rotterdam
Rotterdam, The Netherlands
1 h-index
1 publications
33 citations
Institute of Science and Technology Austria
Klosterneuburg, Austria
1 h-index
4 publications
68 citations

University of Macau
Macao, Macao
1 h-index
1 publications
23 citations
Kansas State University
Manhattan, United States
1 h-index
2 publications
34 citations
Politecnico di Milano
Milan, Italy
1 h-index
2 publications
28 citations

Delft University of Technology
Delft, The Netherlands
1 h-index
1 publications
14 citations

Hong Kong University of Science and Technology
Hong Kong, Hong Kong
1 h-index
1 publications
14 citations

Tilburg University
Tilburg, The Netherlands
1 h-index
1 publications
33 citations
1–8 of 11
1 publications · 23 citations
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Repository · 1 publications · 12 citations
1
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1 publications · 33 citations
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1 publications · 10 citations
1
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1 publications · 14 citations
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