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A Maximal Correlation Framework for Fair Machine Learning

As machine learning algorithms grow in popularity and diversify to many industries, ethical and legal concerns regarding their fairness have become increasingly relevant. We explore the problem of algorithmic fairness, taking an information–theoretic view. The maximal correlation framework is introd...

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Bibliografische gegevens
Hoofdauteurs: Joshua Lee, Yuheng Bu, Prasanna Sattigeri, Rameswar Panda, Gregory W. Wornell, Leonid Karlinsky, Rogerio Schmidt Feris
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: MDPI AG 2022-03-01
Reeks:Entropy
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Online toegang:https://www.mdpi.com/1099-4300/24/4/461
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