Research map / Learning theory and algorithms / Submodular and game algorithms
Rank Aggregation Using Scoring Rules
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Sequential-Winner rather than Sequential-Loser or Score with Plurality | Plurality rank aggregation · Mallows profiles | normalized swap distance to Kemeny ranking: 0.004 | Helped |
| Use Sequential-Winner rather than Sequential-Loser or Score with Plurality | Plurality rank aggregation · Euclidean profiles, d = 1 | normalized swap distance to Kemeny ranking: 0.43 versus 0.27 | Helped |
| Use Sequential-Loser or Score rather than Sequential-Winner with Plurality | Plurality rank aggregation · Mallows profiles with normphi ≤ 0.3 | normalized swap distance to Kemeny ranking | Hurt |
| Use Borda scoring methods | Borda rank aggregation · Mallows profiles | normalized swap distance to Kemeny ranking: from 0 to around 0.1 | Mixed |
| Use Sequential-Loser rather than Sequential-Winner for Plurality | Rank aggregation · Top positions | agreement with Kemeny ranking | Helped |
| Use Sequential-Winner rather than Sequential-Loser for Plurality | Rank aggregation · Bottom positions | agreement with Kemeny ranking | Helped |
| Use Sequential-Winner rather than Sequential-Loser or Score with Plurality | Plurality rank aggregation · Mallows profiles with normphi ≤ 0.3 | number of rounds with ties | Helped |
| Increase the number of voters | Plurality and Borda rank aggregation · Mallows and Euclidean profiles | pairwise normalized swap distance between methods | Helped |
| Use Borda rather than Plurality | Score, Sequential-Winner, and Sequential-Loser · Euclidean profiles | agreement among the three methods | Helped |
Closest papers by meaning
- Optimizing Positional Scoring Rules for Rank Aggregation (AAAI 2017 · similarity 0.90)
- Ranking Wily People Who Rank Each Other (AAAI 2018 · similarity 0.89)
- Refined Characterizations of Approval-Based Committee Scoring Rules (AAAI 2024 · similarity 0.86)
- Selective Preference Aggregation (ICML 2025 · similarity 0.85)
- The Surprising Effectiveness of SP Voting with Partial Preferences (NeurIPS 2024 · similarity 0.85)
- Decentralized Ranking Aggregation via Gossip: Convergence and Robustness (NeurIPS 2026 · similarity 0.85)
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