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Found 2 papers, 1 papers with code
Privacy Constrained Fairness Estimation for Decision Trees
We show that using the Laplacian mechanism, the method is able to estimate SP with low error while guaranteeing the privacy of the individuals in the dataset with high certainty.
Bursting the Burden Bubble? An Assessment of Sharma et al.'s Counterfactual-based Fairness Metric
Metrics are needed to evaluate the fairness of a model.
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