Fairness Classification on ADULT (test)
20.27RiskFair Self-Bounding Learning Algorithm
Evaluation Results
| Method | Links | |||||||
|---|---|---|---|---|---|---|---|---|
| Fair Self-Bounding Learning AlgorithmSens. attr.=GENDER, Type=deterministic, Optimized fairness measure=DP2026.02 | 20.27 | 3.75 | — | — | — | — | — | |
| Fair Self-Bounding Learning AlgorithmSens. attr.=GENDER, Type=deterministic, Optimized fairness measure=EO2026.02 | 20.27 | — | 0.76 | — | — | — | — | |
| Fair Self-Bounding Learning AlgorithmSens. attr.=GENDER, Type=stochastic, Optimized fairness measure=EO2026.02 | 20.27 | — | 0.76 | — | — | — | — | |
| O1Sens. attr.=GENDER, Type=stochastic, Optimized fairness measure=EO2026.02 | 20.27 | — | 0.76 | — | — | — | — | |
| Fair Self-Bounding Learning AlgorithmSens. attr.=GENDER, Type=deterministic, Optimized fairness measure=EOP2026.02 | 20.27 | — | — | 1.75 | — | — | — | |
| Fair Self-Bounding Learning AlgorithmSens. attr.=GENDER, Type=stochastic, Optimized fairness measure=DP2026.02 | 42.64 | 0.93 | — | — | — | — | — | |
| O1Sens. attr.=GENDER, Type=stochastic, Optimized fairness measure=DP2026.02 | 42.64 | 0.93 | — | — | — | — | — | |
| Fair Self-Bounding Learning AlgorithmSens. attr.=GENDER, Type=stochastic, Optimized fairness measure=EOP2026.02 | 42.64 | — | — | 0.43 | — | — | — | |
| O1Sens. attr.=GENDER, Type=stochastic, Optimized fairness measure=EOP2026.02 | 42.64 | — | — | 0.43 | — | — | — | |
| O2Sens. attr.=GENDER, Type=stochastic, Optimized fairness measure=EOP2026.02 | 46.02 | — | — | 0.08 | — | — | — | |
| O2Sens. attr.=GENDER, Type=stochastic, Optimized fairness measure=DP2026.02 | 49.6 | 0.01 | — | — | — | — | — | |
| DualProjAveraging=4 random seeds2026.05 | — | — | — | — | 79.02 | 53.97 | 6.2 | |
| DualProj*Averaging=4 random seeds2026.05 | — | — | — | — | 78.55 | 53.69 | 6.63 | |
| MAS-RandStrategy=Random scheduling, Averaging=4 random seeds2026.05 | — | — | — | — | 76.42 | 60.9 | 7.45 | |
| MAS-RR(1k)Strategy=Round-robin scheduling, Interval=1k, Averaging=4 random seeds2026.05 | — | — | — | — | 76.41 | 60.94 | 7.48 | |
| MAS-RR(2.5k)Strategy=Round-robin scheduling, Interval=2.5k, Averaging=4 random seeds2026.05 | — | — | — | — | 76.25 | 60.56 | 7.69 | |
| MGDAAveraging=4 random seeds2026.05 | — | — | — | — | 75.7 | 61.04 | 7.56 | |
| Nash-MTL*Averaging=4 random seeds2026.05 | — | — | — | — | 76.19 | 58.96 | 7.08 | |
| UPGradAveraging=4 random seeds2026.05 | — | — | — | — | 77.66 | 62.36 | 6.97 | |
| UPGrad*Averaging=4 random seeds2026.05 | — | — | — | — | 76.75 | 60.18 | 7.37 |