Most Expected Winner: An Interpretation of Winners over Uncertain Voter Preferences
Summary: Introduces MEW for uncertain voters, separating generation from observation to yield a unified incomplete+probabilistic voting profile. Proves MEW hardness; tractable RIM/Mallows cases with solvers and pruning; validated on real and synthetic benchmarks. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Haoyue Ping
- 2. Julia Stoyanovich
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,804 | A System for Management and Analysis of Preference Data | 2014 | VLDB | 5.906327e-05 |
| 8,539 | Querying Probabilistic Preferences in Databases | 2017 | PODS | 4.4893996e-05 |
| 13,294 | Supporting Hard Queries over Probabilistic Preferences | 2020 | VLDB | - |
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