A Canonical Data Transformation for Achieving Inter- and Within-Group Fairness-Reference-Cited by-同舟云学术

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A Canonical Data Transformation for Achieving Inter- and Within-Group Fairness

Published:2024 Issue: Volume:19 Page:7449-7464
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Lazri Zachary McBride¹^ORCID,Brugere Ivan²,Tian Xin³^ORCID,Dachman-Soled Dana¹^ORCID,Polychroniadou Antigoni²,Dervovic Danial²^ORCID,Wu Min¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering (ECE), University of Maryland Institute for Advanced Computer Studies (UMIACS), University of Maryland, College Park, MD, USA

2. J.P. Morgan AI Research, New York, NY, USA

3. Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA

Funder

NSF

J.P. Morgan Chase Artificial Intelligence (AI) Faculty Research Award

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/10206/10319981/10559875-aam.pdf

Reference49 articles.

1. Bias detection by using name disparity tables across protected groups

2. Machine Bias *

3. Discrimination in online ad delivery

4. Amazon Scraps Secret AI Recruiting Tool that Showed Bias against Women *

5. Machine Learning and Health Care Disparities in Dermatology

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