Machine learning fairness notions: Bridging the gap with real-world applications

Volume: 58, Issue: 5, Pages: 102642 - 102642
Published: Sep 1, 2021
Abstract
Fairness emerged as an important requirement to guarantee that Machine Learning (ML) predictive systems do not discriminate against specific individuals or entire sub-populations, in particular, minorities. Given the inherent subjectivity of viewing the concept of fairness, several notions of fairness have been introduced in the literature. This paper is a survey that illustrates the subtleties between fairness notions through a large number of...
Paper Details
Title
Machine learning fairness notions: Bridging the gap with real-world applications
Published Date
Sep 1, 2021
Volume
58
Issue
5
Pages
102642 - 102642
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