Research map / Learning theory and algorithms / Fairness
Faster Fair Machine via Transferring Fairness Constraints to Virtual Samples
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Transfer demographic-parity constraints to virtual samples and solve with SVM | SVM · Adult, CelebA, Dutch | running time | Helped |
| Transfer demographic-parity constraints to virtual samples and solve with SVM | SVM · Adult, CelebA, COMPAS, Dutch | accuracy | No clear effect |
| Transfer demographic-parity constraints to virtual samples and solve with SVM | SVM · Adult, CelebA, COMPAS, Dutch | demographic parity | No clear effect |
| Transfer false-positive-rate constraints to virtual samples and solve with SVM | SVM · Adult, CelebA, Dutch | running time | Helped |
| Transfer false-positive-rate constraints to virtual samples and solve with SVM | SVM · Adult, CelebA, COMPAS, Dutch | accuracy | No clear effect |
| Transfer false-positive-rate constraints to virtual samples and solve with SVM | SVM · Adult, CelebA, COMPAS, Dutch | false-positive rate | No clear effect |
| Construct virtual samples for multiple fairness constraints | SVM · COMPAS, SynthOpp, SynthSame | false-positive rate and false-negative rate | Helped |
Closest papers by meaning
- FaiREE: fair classification with finite-sample and distribution-free guarantee (ICLR 2023 · similarity 0.88)
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- fairret: a Framework for Differentiable Fairness Regularization Terms (ICLR 2024 · similarity 0.87)
- The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning (NeurIPS 2024 · similarity 0.87)
- Learning with Statistical Equality Constraints (NeurIPS 2025 · similarity 0.86)
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