Proportional Representation under Single-Crossing Preferences Revisited
Andrei Costin Constantinescu, Edith Elkind
摘要
We study the complexity of determining a winning committee under the Chamberlin-Courant voting rule when voters' preferences are single-crossing on a line, or, more generally, on a median graph (this class of graphs includes, e.g., trees and grids). For the line, Skowron et al. (2015) describe an O(n 2 mk) algorithm (where n, m, k are the number of voters, the number of candidates and the committee size, respectively); we show that a simple tweak improves the time complexity to O(nmk). We then improve this bound for k = Ω(log n) by reducing our problem to the k-link path problem for DAGs with concave Monge weights, obtaining a nm2 O( √ log k log log n) algorithm for the general case and a nearly linear algorithm for the Borda misrepresentation function. For trees, we point out an issue with the algorithm proposed by Clearwater, Puppe, and Slinko (2015), and develop a O(nmk) algorithm for this case as well. For grids, we formulate a conjecture about the structure of optimal solutions, and describe a polynomial-time algorithm that finds a winning committee if this conjecture is true; we also explain how to convert this algorithm into a bicriterial approximation algorithm whose correctness does not depend on the conjecture.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper1
问问它们各自怎么用它相关 Paper
- Approval-Based Committee Voting under Incomplete InformationAviram Imber, Jonas Israel, Markus Brill, Benny KimelfeldAAAI 2022 · 被引用 10 次
- Multiagent MST Cover: Pleasing All Optimally via a Simple Voting RuleBo Li, Xiaowei Wu, Chenyang Xu, Ruilong ZhangAAAI 2023 · 被引用 1 次
- On the Distortion of Committee Election with 1-Euclidean Preferences and Few Distance QueriesDimitris Fotakis, Laurent Gourvès, Panagiotis PatsilinakosAAAI 2025 · 被引用 2 次
- Approximating (k, ℓ-Median Clustering for Polygonal CurvesMaike Buchin, Anne Driemel, Dennis RohdeSODA 2021 · 被引用 6 次
- Bi-Criteria Metric DistortionKiarash Banihashem, Diptarka Chakraborty, Shayan Chashm Jahan, Iman Gholami 等ICLR 2026
