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Improving Fair Training under Correlation Shifts

ICML 2023 · Learning theory and algorithms › Fairness · approach: Post-processing and transport for fairness · 0 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Pre-processing for correlation shift (sampling to adjust (y,z) class ratios) before in-processingFairBatch (FB) · Synthetic test (corr. 50% of train), DPDP unfairness: 0.048 -> 0.003Helped
Pre-processing for correlation shift before in-processingFairness Constraints (FC) · Synthetic test, DPDP unfairness: 0.038 -> 0.034Helped
Pre-processing for correlation shift before in-processingAdversarial Debiasing (AD) · Synthetic test, DPDP unfairness: 0.032 -> 0.017Helped
Pre-processing for correlation shift before in-processingFairBatch, FC, AD · Synthetic test, DPaccuracy: FB +0.015, FC +0.071, AD +0.052 (ours higher); Ours+AD lower than RWMixed
Reweighing (RW) pre-processing before in-processingFairBatch · Synthetic test, DPDP unfairness: 0.048 -> 0.055Hurt
Pre-processing for correlation shift before in-processingFairBatch, DP single metric · COMPAS testDP unfairness: 0.038 -> 0.027Helped
Pre-processing for correlation shift before in-processingAdversarial Debiasing, DP single metric · COMPAS testDP unfairness: 0.054 -> 0.045 (improves) ; accuracy 0.655 -> 0.650Hurt
Pre-processing for correlation shift before in-processingFairness Constraints, DP single metric · COMPAS testDP unfairness: 0.050 -> 0.037 with std 0.021 overlappingNo clear effect
Pre-processing for correlation shift before FairBatch, DP and EO jointlyFairBatch, multiple metrics · Synthetic test, DP & EOmax(DP, EO) unfairness: 0.091 -> 0.058Helped
Pre-processing for correlation shift before fairness constraints, DP and EO jointlyFairness Constraints · COMPAS, DP & EOmax(DP, EO) unfairness: 0.137 -> 0.106Helped
Pre-processing for correlation shift before FairBatch, DP and EO jointlyFairBatch · COMPAS, DP & EOmax(DP, EO) unfairness: 0.187 -> 0.130Helped
Pre-processing for correlation shift before in-processing when correlation shift is large (test corr. 10% of train) (ablation)FairBatch · Synthetic, varying test correlationDP unfairness: 0.108 -> 0.003Helped

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