17 citations · 25 across the 3 of their papers we have counts for
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cs.LG2020
Debiasing classifiers: is reality at variance with expectation?
Ashrya Agrawal, Florian Pfisterer, Bernd Bischl +5
We present an empirical study of debiasing methods for classifiers, showing that debiasers often fail in practice to generalize out-of-sample, and can in fact make fairness worse r…
stat.ML2020★ 7 cited
Model updating after interventions paradoxically introduces bias
James Liley, Samuel R Emerson, Bilal A Mateen +3
Machine learning is increasingly being used to generate prediction models for use in a number of real-world settings, from credit risk assessment to clinical decision support. Rece…