Proportional Representation under Single-Crossing Preferences Revisited

Authors: Andrei Costin Constantinescu, Edith Elkind5286-5293

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Reproducibility Variable Result LLM Response
Research Type Theoretical 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 tree. For the line, Skowron et al. (2015) describe an O(n2mk) 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 nm2O( 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.
Researcher Affiliation Academia Andrei Costin Constantinescu, Edith Elkind University of Oxford
Pseudocode No The paper describes algorithms (dynamic programming, reduction) but does not contain structured pseudocode or algorithm blocks.
Open Source Code No The paper states: "Full version The full version of the paper is available on arXiv (Constantinescu and Elkind 2020).". This is a preprint server for papers, not a code repository. No other concrete access to source code is provided.
Open Datasets No The paper describes theoretical algorithms and complexity analysis. It does not use or refer to any publicly available datasets for training or evaluation.
Dataset Splits No The paper describes theoretical algorithms and complexity analysis. It does not involve experimental validation with dataset splits.
Hardware Specification No The paper is theoretical and focuses on algorithm complexity. It does not mention any specific hardware used for running experiments.
Software Dependencies No The paper describes algorithms theoretically and does not specify any software dependencies with version numbers.
Experiment Setup No The paper is theoretical and focuses on algorithm design and complexity. It does not describe an experimental setup, hyperparameters, or training configurations.