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  Fairness Constraints: A Flexible Approach for Fair Classification

Zafar, M. B., Valera, I., Gomez Rodriguez, M., & Gummadi, K. (2019). Fairness Constraints: A Flexible Approach for Fair Classification. Journal of Machine Learning Research, 20: 75.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0005-FAA2-A Version Permalink: https://hdl.handle.net/21.11116/0000-0005-FAA3-9
Genre: Journal Article
Latex : Fairness Constraints: {A} Flexible Approach for Fair Classification

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http://jmlr.org/papers/v20/18-262.html (Publisher version)
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 Creators:
Zafar, Muhammad Bilal1, Author           
Valera, Isabel2, Author           
Gomez Rodriguez, Manuel3, Author           
Gummadi, Krishna1, Author           
Affiliations:
1Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society, ou_2105291              
2External Organizations, ou_persistent22              
3Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Dates: 2019
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: -
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Title: Journal of Machine Learning Research
Source Genre: Journal
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Publ. Info: Brookline, MA : Microtome Publishing
Pages: 42 p. Volume / Issue: 20 Sequence Number: 75 Start / End Page: - Identifier: ISSN: 1532-4435
CoNE: https://pure.mpg.de/cone/journals/resource/111002212682020