Introduces learning-augmented robust algorithmic recourse that trades off consistency with accurate future-model predictions against robustness to inaccurate predictions via a novel algorithm.
fairmlbook.org, 2019
2 Pith papers cite this work. Polarity classification is still indexing.
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Short-term group fairness in repeated selections can incur a high price of fairness even with nearly identical group distributions, but long-term disparities can vanish under simple investment policies with low PoF.
citing papers explorer
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Learning-Augmented Robust Algorithmic Recourse
Introduces learning-augmented robust algorithmic recourse that trades off consistency with accurate future-model predictions against robustness to inaccurate predictions via a novel algorithm.
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Price of Fairness in Short-Term and Long-Term Algorithmic Selections
Short-term group fairness in repeated selections can incur a high price of fairness even with nearly identical group distributions, but long-term disparities can vanish under simple investment policies with low PoF.