Research map / Graph learning / Graph algorithms and clustering
Beyond Pairwise Comparisons in Social Choice: A Setwise Kemeny Aggregation Problem
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| increase k from 2 to 9 | k-wise Kemeny DP · Mallows phi~1, m=18 | avg number of consensus rankings: 19.7 -> 4.12 | Helped |
| increase k from 2 to 18 (k=m) | k-wise Kemeny DP · Mallows phi~1, m=18 | avg number of consensus rankings: 19.7 -> 1.47 | Helped |
| increase k from 2 to 14 | k-wise Kemeny DP · Mallows phi~1, m=14 | avg number of consensus rankings: 5.36 -> 1.16 | Helped |
| increase k from 2 to 18 | k-wise Kemeny DP · Mallows phi~1, m=18 | average running time (s): 70.93 -> 74.95 | No clear effect |
| increase m from 14 to 18 | k-wise Kemeny DP · Mallows phi~1, k=2 | average running time (s): 2.52 -> 70.93 | Hurt |
| add 3-wise majority graph preprocessing (ablation) | DP for 3-KAP · m=18, phi=0.5 | average time (s): 71.17 -> 0.20 | Helped |
| add 3-wise majority graph preprocessing (ablation) | DP for 3-KAP · m=14, phi=0.9 | average time (s): 2.52 -> 0.94 | Helped |
| add preprocessing when voters are nearly uncorrelated (ablation) | DP for 3-KAP · m=18, phi=0.95 | average time (s): 71.17 -> 61.72 | Helped |
| increase Mallows dispersion phi from 0.8 to 0.95 with preprocessing | DP for 3-KAP · m=18 | average time (s): 0.20 -> 61.72 | Hurt |
| increase Mallows dispersion phi from 0.81 to 0.95 | 3-wise majority digraph · m=18 | average largest SCC size: 2.84 -> 17.44 | Hurt |
Closest papers by meaning
- Selective Preference Aggregation (ICML 2025 · similarity 0.90)
- Eliciting Kemeny Rankings (AAAI 2024 · similarity 0.86)
- Constant-Factor Distortion Mechanisms for k-Committee Election (AAAI 2025 · similarity 0.86)
- Aggregating Quantitative Relative Judgments: From Social Choice to Ranking Prediction (NeurIPS 2024 · similarity 0.86)
- Computing Voting Rules with Improvement Feedback (ICML 2025 · similarity 0.86)
- The Surprising Effectiveness of SP Voting with Partial Preferences (NeurIPS 2024 · similarity 0.85)
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