Research map / Label-efficient and robust learning / Domain adaptation and generalization
What Do Multiwinner Voting Rules Do? An Experiment Over the Two-Dimensional Euclidean Domain
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use Bloc instead of STV | multiwinner rule · 2D Euclidean elections | variance of winners per quadrant: 17.789 vs 0.994 (uniform square) | Hurt |
| use SNTV instead of STV | multiwinner rule · 2D Euclidean elections | variance of winners per quadrant: 3.292 vs 0.994 (uniform square) | Hurt |
| use STV instead of SNTV | parliamentary election rule · 2D Euclidean elections | variance of winners per quadrant: 3.275 -> 1.150 (Gaussian) | Helped |
| use alpha_k-PAV instead of k-Borda | multiwinner rule · 2D Euclidean elections | variance of winners per quadrant: 4.605 -> 1.323 (uniform square) | Helped |
Closest papers by meaning
- Temporal Fairness in Multiwinner Voting (AAAI 2024 · similarity 0.91)
- An Analysis of Approval-Based Committee Rules for 2D-Euclidean Elections (AAAI 2021 · similarity 0.90)
- The Metric Distortion of Multiwinner Voting (AAAI 2022 · similarity 0.88)
- Maintaining Proportional Committees with Dynamic Candidate Sets (ICML 2025 · similarity 0.87)
- Spatial Voting with Incomplete Voter Information (AAAI 2024 · similarity 0.86)
- Verifying Proportionality in Temporal Voting (AAAI 2025 · similarity 0.85)
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