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  Economic Theories of Distributive Justice for Fair Machine Learning

Gummadi, K., & Heidari, H. (2019). Economic Theories of Distributive Justice for Fair Machine Learning. In Proceedings of The World Wide Web Conference (pp. 1301-1302). New York, NY: ACM. doi:10.1145/3308560.3320101.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0006-03CD-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0009-CE4D-A
Genre: Conference Paper

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3308560.3320101.pdf (Publisher version), 337KB
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This paper is published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license. Authors reserve their rights to disseminate the work on their personal and corporate Web sites with the appropriate attribution. WWW ’19 Companion, May 13–17, 2019, San Francisco, CA, USA © 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License. ACM ISBN 978-1-4503-6675-5/19/05. https://doi.org/10.1145/3308560.3320101
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 Creators:
Gummadi, Krishna1, Author           
Heidari, Hoda2, Author
Affiliations:
1Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society, ou_2105291              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 201920192019
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Gummadi_WWW2019
DOI: 10.1145/3308560.3320101
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Title: The Web Conference
Place of Event: San Francisco, CA, USA
Start-/End Date: 2019-05-13 - 2019-05-17

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Title: Proceedings of The World Wide Web Conference
  Abbreviation : WWW 2019
Source Genre: Proceedings
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Publ. Info: New York, NY : ACM
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1301 - 1302 Identifier: ISBN: 978-1-4503-6674-8