29 citations · 72 across the 8 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.SE2022★ 2 cited
Enhanced Fairness Testing via Generating Effective Initial Individual Discriminatory Instances
Minghua Ma, Zhao Tian, Max Hort +4
Fairness testing aims at mitigating unintended discrimination in the decision-making process of data-driven AI systems. Individual discrimination may occur when an AI model makes d…
cs.SE2022★ 29 cited
Fairness Testing: A Comprehensive Survey and Analysis of Trends
Zhenpeng Chen, Jie M. Zhang, Max Hort +2
Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and concern among software engineers. To tackle this issue, extensive research has been dedica…
cs.LG2022★ 24 cited
Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey
Max Hort, Zhenpeng Chen, Jie M. Zhang +2
This paper provides a comprehensive survey of bias mitigation methods for achieving fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning bias…