How to be fair? A study of label and selection bias

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Machine learning - ISSN 0885-6125-112 (2023) p. 5081-5104
Auteur(s)

Users’ needs in interactive bias auditing tools introducing a requirement checklist and evaluating existing tools

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AI and ethics - ISSN 2730-5953- (2023) p. 1-29

Artificial Intelligence and Machine Learning : 34th Joint Benelux Conference, BNAIC/Benelearn 2022, November 7–9, 2022, Mechelen, Belgium

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Cham, Springer, 2023,179 p.
Auteur(s)

Real-life performance of fairness interventions : introducing a new benchmarking dataset for fair ML

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Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing (SAC '23), March 27 – March 31, 2023, Tallinn, Estonia- () p. 350-357