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Much of the previous machine learning (ML) fairness literature assumes that protected features such as race and sex are present in the dataset, and relies upon them to mitigate fairness concerns.
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Cited alongside, same era.
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Environment Inference for Invariant Learning. In ICML Workshop on Uncertainty and Robustness
Elliot Creager, Jörn-Henrik Jacobsen, and Richard Zemel. 2020 · 2020
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