Research map / Learning theory and algorithms / Fairness
Recycling Privileged Learning and Distribution Matching for Fairness
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add MMD distribution matching fairness constraint to SVM | SVM · ProPublica COMPAS | |TPR z=0 - TPR z=1|: 0.2573±0.0158 -> 0.1169±0.0690 | Helped |
| add MMD distribution matching fairness constraint to SVM | SVM · ProPublica COMPAS | accuracy: 0.6367±0.0212 -> 0.5931±0.0599 | Hurt |
| add MMD distribution matching fairness constraint to SVM | SVM · Adult | |Acc z=0 - Acc z=1|: 0.1136±0.0064 -> 0.0640±0.0280 | Helped |
| add MMD distribution matching fairness constraint to SVM | SVM · Adult | accuracy: 0.8457±0.0034 -> 0.8152±0.0068 | Hurt |
| add privileged learning (protected attribute as privileged info) to DM (ablation) | DM (L-BFGS) · ProPublica COMPAS | |TPR z=0 - TPR z=1|: 0.1169±0.0690 -> 0.1065±0.0413 | Helped |
| add privileged learning to DM (ablation) | DM (L-BFGS) · Adult | |Acc z=0 - Acc z=1|: 0.0640±0.0280 -> 0.0459±0.0372 | Helped |
| add privileged learning to DM (ablation) | DM (L-BFGS) · ProPublica COMPAS | accuracy: 0.5931±0.0599 -> 0.6089±0.0398 | Helped |
| add privileged learning to DM (ablation) | DM (L-BFGS) · Adult | accuracy: 0.8152±0.0068 -> 0.8127±0.0134 | No clear effect |
| use EMO Pareto frontier operating point instead of L-BFGS single solution (ablation) | DM · Adult | |Acc z=0 - Acc z=1|: 0.0640±0.0280 -> 0.0388±0.0179 | Helped |
| use CCP optimization instead of L-BFGS (ablation) | DM · ProPublica COMPAS | fairness constraint satisfaction | Hurt |
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