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  A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices

Speicher, T., Heidari, H., Grgić-Hlača, N., Gummadi, K. P., Singla, A., Weller, A., et al. (2018). A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices. In KDD'18 (pp. 2239-2248). New York, NY: ACM. doi:10.1145/3219819.3220046.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0003-47C6-E Version Permalink: https://hdl.handle.net/21.11116/0000-000E-7F1E-4
Genre: Conference Paper
Latex : A Unified Approach to Quantifying Algorithmic Unfairness: {M}easuring Individual & Group Unfairness via Inequality Indices

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3219819.3220046.pdf (Publisher version), 3MB
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This work is licensed under a Creative Commons Attribution International 4.0 License KDD ’18, August 19–23, 2018, London, United Kingdom ©2018 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-5552-0/18/08.
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https://creativecommons.org/licenses/by/4.0/

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 Creators:
Speicher, Till1, Author           
Heidari, Hoda2, Author
Grgić-Hlača, Nina1, Author           
Gummadi, Krishna P.1, Author           
Singla, Adish3, Author                 
Weller, Adrian2, Author
Zafar, Muhammad Bilal1, Author           
Affiliations:
1Group K. Gummadi, Max Planck Institute for Software Systems, Max Planck Society, ou_2105291              
2External Organizations, ou_persistent22              
3Group A. Singla, Max Planck Institute for Software Systems, Max Planck Society, ou_2541698              

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Language(s): eng - English
 Dates: 20182018
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Speicher_KDD2018
DOI: 10.1145/3219819.3220046
 Degree: -

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Title: 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Place of Event: London, UK
Start-/End Date: 2018-08-10 - 2018-08-23

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Project name : FairSocialComputing
Grant ID : 789373
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)

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Title: KDD'18
  Subtitle : Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
  Abbreviation : KDD 2018
Source Genre: Proceedings
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Publ. Info: New York, NY : ACM
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 2239 - 2248 Identifier: ISBN: 978-1-4503-5552-0