Research map / Learning theory and algorithms / Fairness
Achieving Long-Term Fairness in Sequential Decision Making
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use the proposed long-term fairness framework with repeated risk minimization instead of static fairness baselines | Sequential decision models · Synthetic dataset, t=5 | Long: 0.340 -> 0.002 | Helped |
| Use the proposed long-term fairness framework with repeated risk minimization instead of static fairness baselines | Sequential decision models · Semi-synthetic dataset, t=4 | Long: 0.295 -> 0.003 | Helped |
| Use the proposed framework instead of the strongest static fairness baseline | Sequential decision models · Synthetic dataset, t=5 | Short: 0.020 -> 0.002 | Helped |
| Use the proposed framework instead of the strongest static fairness baseline | Sequential decision models · Semi-synthetic dataset, t=4 | Short: 0.012 -> 0.006 | Helped |
| Use the proposed fairness framework instead of the highest-accuracy baseline | Sequential decision models · Synthetic dataset, t=5 | Acc: 0.917 -> 0.692 | Hurt |
| Use the proposed fairness framework instead of the highest-accuracy baseline | Sequential decision models · Semi-synthetic dataset, t=4 | Acc: 0.841 -> 0.687 | Hurt |
| Use repeated risk minimization when decision sensitivity is reasonably small | Proposed method · Synthetic dataset | convergence | Helped |
Closest papers by meaning
- Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate (ICML 2024 · similarity 0.90)
- Long-Term Fair Decision Making through Deep Generative Models (AAAI 2024 · similarity 0.89)
- Remembering to Be Fair: Non-Markovian Fairness in Sequential Decision Making (ICML 2024 · similarity 0.88)
- A Causal Lens for Learning Long-term Fair Policies (ICLR 2025 · similarity 0.88)
- A Local Method for Satisfying Interventional Fairness with Partially Known Causal Graphs (NeurIPS 2024 · similarity 0.86)
- Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach (ICLR 2024 · similarity 0.85)
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