PAFER estimates statistical parity for differentially private decision trees using Laplacian noise, achieving low error while preserving privacy and favoring interpretable trees.
Official Journal of the European Union L 119 , 1–88 (14-04-2016)
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Privacy Constrained Fairness Estimation for Decision Trees
PAFER estimates statistical parity for differentially private decision trees using Laplacian noise, achieving low error while preserving privacy and favoring interpretable trees.