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In algorithmically fair prediction problems, a standard goal is to ensure the equality of fairness metrics across multiple overlapping groups simultaneously.
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L. Elisa Celis, Lingxiao Huang, Vijay Keswani, and Nisheeth K. Vishnoi · 2018
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Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
Andrew Cotter, Maya Gupta, Heinrich Jiang, Nathan Srebro, Karthik Sridharan, Serena Wang, Blake Woodworth, and Seungil You · 2018
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James Foulds, Rashidul Islam, Kamrun Naher Keya, and Shimei Pan · 2018
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Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nathan Srebro
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