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  From Parity to Preference-based Notions of Fairness in Classification

Zafar, M. B., Valera, I., Gomez Rodriguez, M., Gummadi, K., & Weller, A. (2017). From Parity to Preference-based Notions of Fairness in Classification. In Fairness, Accountability, and Transparency in Machine Learning.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0000-C6AA-1 Version Permalink: https://hdl.handle.net/21.11116/0000-0000-C6AB-0
Genre: Conference Paper

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from_parity_to_preference_notions_of_fairness.pdf (Publisher version), 257KB
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 Creators:
Zafar, Muhammad Bilal1, Author           
Valera, Isabel2, Author
Gomez Rodriguez, Manuel2, Author           
Gummadi, Krishna1, Author           
Weller, Adrian1, Author
Affiliations:
1Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society, ou_2105291              
2Group M. Gomez Rodriguez, Max Planck Institute for Software Systems, Max Planck Society, ou_2105290              

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Language(s): eng - English
 Dates: 2017
 Publication Status: Published online
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 Identifiers: BibTex Citekey: ZafarFATML2017
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Title: 4th Workshop on Fairness, Accountability, and Transparency in Machine Learning
Place of Event: Halifax, Canada
Start-/End Date: 2017-08-14 - 2017-08-14

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Title: Fairness, Accountability, and Transparency in Machine Learning
  Abbreviation : FAT/ML 2017
  Other : FATML 2017
  Subtitle : FAT/ML 2017 Papers
Source Genre: Proceedings
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