Black box fairness testing of machine learning models-Reference-Cited by-同舟云学术

Black box fairness testing of machine learning models

Published:2019-08-12 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
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Author:

Aggarwal Aniya¹,Lohia Pranay¹,Nagar Seema¹,Dey Kuntal¹,Saha Diptikalyan¹

Affiliation:

1. IBM Research, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3338906.3338937

Reference25 articles.

1. Julius Adebayo and Lalana Kagal. 2016. Iterative Orthogonal Feature Projection for Diagnosing Bias in Black-Box Models. arXiv: arXiv:1611.04967 Julius Adebayo and Lalana Kagal. 2016. Iterative Orthogonal Feature Projection for Diagnosing Bias in Black-Box Models. arXiv: arXiv:1611.04967

2. EXE

3. Fairness through awareness

4. Certifying and Removing Disparate Impact

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