Research map / Learning theory and algorithms / Fairness
Policy Learning for Fairness in Ranking
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use PG-Rank with a neural network instead of a linear model | PG-Rank · Yahoo! SET 1 test | NDCG@10 | Helped |
| Use PG-Rank with a linear model instead of RankSVM | Yahoo! SET 1 test · Yahoo! SET 1 test | NDCG@10: 0.75924 -> 0.76145 | Helped |
| Use PG-Rank with a linear model instead of RankSVM | Yahoo! SET 1 test · Yahoo! SET 1 test | ERR: 0.43680 -> 0.44988 | Helped |
| Increase the fairness weight lambda | Fair-PG-Rank with a linear model · Synthetic ranking data | Group disparity | Helped |
| Increase the fairness weight lambda | Fair-PG-Rank with a linear model · Synthetic ranking data | NDCG | Mixed |
| Use fairness-aware policy learning rather than post-processing predicted relevances | Synthetic ranking data · Synthetic ranking data | Group disparity | Helped |
| Use fairness-aware policy learning rather than the heuristic baseline | Synthetic ranking data · Synthetic ranking data | Group disparity | Helped |
| Increase the fairness weight lambda | Fair-PG-Rank with a linear model · Yahoo! Learning to Rank | Individual disparity | Helped |
| Increase the fairness weight lambda | Fair-PG-Rank with a neural network · Yahoo! Learning to Rank | Individual disparity | Helped |
| Increase the fairness weight lambda | Fair-PG-Rank with a linear model · German Credit | Group disparity | Helped |
| Use Fair-PG-Rank rather than the baselines | German Credit · German Credit | Group disparity | Helped |
Closest papers by meaning
- Stability and Multigroup Fairness in Ranking with Uncertain Predictions (ICML 2024 · similarity 0.87)
- FairJob: A Real-World Dataset for Fairness in Online Systems (NeurIPS 2024 · similarity 0.85)
- A Causal Lens for Learning Long-term Fair Policies (ICLR 2025 · similarity 0.85)
- Interpolating Item and User Fairness in Multi-Sided Recommendations (NeurIPS 2024 · similarity 0.85)
- Learning Fair Policies for Multi-Stage Selection Problems from Observational Data (AAAI 2024 · similarity 0.85)
- Adapting Static Fairness to Sequential Decision-Making: Bias Mitigation Strategies towards Equal Long-term Benefit Rate (ICML 2024 · similarity 0.85)
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