Fairness Improvement with Multiple Protected Attributes: How Far Are We?-Reference-Cited by-同舟云学术

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Fairness Improvement with Multiple Protected Attributes: How Far Are We?

Published:2024-04-12 Issue: Volume:2021 Page:1-13
ISSN:
Container-title:Proceedings of the IEEE/ACM 46th International Conference on Software Engineering
language:
Short-container-title:

Author:

Chen Zhenpeng¹^ORCID,Zhang Jie M.²^ORCID,Sarro Federica¹^ORCID,Harman Mark¹^ORCID

Affiliation:

1. University College London, London, United Kingdom

2. King's College London, London, United Kingdom

Funder

ERC Advanced Grant

UKRI Trustworthy Autonomous Systems Node in Verifiability

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3597503.3639083

Reference70 articles.

1. 1996. The Adult Census Income dataset. https://archive.ics.uci.edu/ml/datasets/adult.

2. 2003. U.S. Equal Employment Opportunity Commission. https://www.eeoc.gov/initiatives/e-race/significant-eeoc-racecolor-casescovering-private-and-federal-sectors#intersectional.

3. 2015. The Mep15 dataset. https://meps.ahrq.gov/mepsweb/data_stats/download_data_files_detail.jsp?cboPufNumber=HC-181.

4. 2016. The Compas dataset. https://github.com/propublica/compas-analysis.

5. 2016. The Default dataset. https://archive.ics.uci.edu/ml/datasets/default+of+credit+card+clients.

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1. Fairness Testing of Machine Translation Systems;ACM Transactions on Software Engineering and Methodology;2024-06-27

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