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Related papers: Justifying Groups in Multiwinner Approval Voting

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Popular centroid-based clustering methods are typically optimized for global objectives, and may fail to adequately represent large groups of datapoints. Thus, one needs proportionality notions suited for metric settings. Ideally, such…

Computer Science and Game Theory · Computer Science 2026-05-28 Yu He , Jeremy Vollen , Edith Elkind

We characterize the class of committee scoring rules that satisfy the fixed-majority criterion. In some sense, the committee scoring rules in this class are multiwinner analogues of the single-winner Plurality rule, which is uniquely…

Computer Science and Game Theory · Computer Science 2016-03-01 Piotr Faliszewski , Piotr Skowron , Arkadii Slinko , Nimrod Talmon

We consider a committee voting setting in which each voter approves of a subset of candidates and based on the approvals, a target number of candidates are selected. Aziz et al. (2015) proposed two representation axioms called justified…

Computer Science and Game Theory · Computer Science 2017-03-24 Haris Aziz , Shenwei Huang

We examine the following voting situation. A committee of $k$ people is to be formed from a pool of n candidates. The voters selecting the committee will submit a list of $j$ candidates that they would prefer to be on the committee. We…

Combinatorics · Mathematics 2014-02-05 Matt Davis , Michael E. Orrison , Francis Edward Su

We study multiwinner elections with approval-based preferences. An instance of a multiwinner election consists of a set of alternatives, a population of voters---each voter approves a subset of alternatives, and the desired committee size…

Computer Science and Game Theory · Computer Science 2019-10-15 Piotr Skowron

In approval-based multiwinner voting, voters express approval preferences over a set of candidates, and the goal is to return a winning committee. This model captures a broad range of subset selection problems under preferences. Prior work…

Computer Science and Game Theory · Computer Science 2026-04-28 Niclas Boehmer , Luca Kreisel , Jannik Peters

The study of fairness in multiwinner elections focuses on settings where candidates have attributes. However, voters may also be divided into predefined populations under one or more attributes (e.g., "California" and "Illinois" populations…

Computer Science and Game Theory · Computer Science 2022-11-24 Kunal Relia

When selecting committees based on preferences of voters, a variety of different criteria can be considered. Two natural objectives are maximizing the utilitarian welfare (the sum of voters' utilities) and coverage (the number of…

Computer Science and Game Theory · Computer Science 2023-12-14 Markus Brill , Jannik Peters

Fairness in multiwinner elections, a growing line of research in computational social choice, primarily concerns the use of constraints to ensure fairness. Recent work proposed a model to find a diverse \emph{and} representative committee…

Computer Science and Game Theory · Computer Science 2022-11-28 Kunal Relia

We study approval-based committee voting from a novel perspective. While extant work largely centers around proportional representation of the voters, we shift our focus to the candidates while preserving proportionality. Intuitively,…

Computer Science and Game Theory · Computer Science 2025-06-24 Gregory Kehne , Ulrike Schmidt-Kraepelin , Krzysztof Sornat

We introduces a general linear framework that unifies the study of multi-winner voting rules and proportionality axioms, demonstrating that many prominent multi-winner voting rules-including Thiele methods, their sequential variants, and…

Computer Science and Game Theory · Computer Science 2025-03-06 Lirong Xia

Multiwinner voting rules are used to select a small representative subset of candidates or items from a larger set given the preferences of voters. However, if candidates have sensitive attributes such as gender or ethnicity (when selecting…

Computers and Society · Computer Science 2018-06-20 L. Elisa Celis , Lingxiao Huang , Nisheeth K. Vishnoi

The Chamberlin-Courant and Monroe rules are fundamental and well-studied rules in the literature of multi-winner elections. The problem of determining if there exists a committee of size k that has a Chamberlin-Courant (respectively,…

Data Structures and Algorithms · Computer Science 2020-04-30 Chinmay Sonar , Palash Dey , Neeldhara Misra

Real-life tools for decision-making in many critical domains are based on ranking results. With the increasing awareness of algorithmic fairness, recent works have presented measures for fairness in ranking. Many of those definitions…

Machine Learning · Computer Science 2023-07-10 Jinyang Li , Yuval Moskovitch , H. V. Jagadish

When selecting multiple candidates based on approval preferences of agents, the proportional representation of agents' opinions is an important and well-studied desideratum. Existing criteria for evaluating the representativeness of…

Computer Science and Game Theory · Computer Science 2024-10-02 Markus Brill , Jonas Israel , Evi Micha , Jannik Peters

To choose a suitable multiwinner voting rule is a hard and ambiguous task. Depending on the context, it varies widely what constitutes the choice of an ``optimal'' subset of alternatives. In this paper, we provide a quantitative analysis of…

Multiagent Systems · Computer Science 2020-09-01 Martin Lackner , Piotr Skowron

We consider a voting scenario in which the resource to be voted upon may consist of both indivisible and divisible goods. This setting generalizes both the well-studied model of multiwinner voting and the recently introduced model of cake…

Computer Science and Game Theory · Computer Science 2024-10-14 Xinhang Lu , Jannik Peters , Haris Aziz , Xiaohui Bei , Warut Suksompong

A population of voters must elect representatives among themselves to decide on a sequence of possibly unforeseen binary issues. Voters care only about the final decision, not the elected representatives. The disutility of a voter is…

Computer Science and Game Theory · Computer Science 2020-06-16 Reshef Meir , Fedor Sandomirskiy , Moshe Tennenholtz

In this work, we define and solve the Fair Top-k Ranking problem, in which we want to determine a subset of k candidates from a large pool of n >> k candidates, maximizing utility (i.e., select the "best" candidates) subject to group…

Computers and Society · Computer Science 2018-07-03 Meike Zehlike , Francesco Bonchi , Carlos Castillo , Sara Hajian , Mohamed Megahed , Ricardo Baeza-Yates

Multicalibration is a notion of fairness for predictors that requires them to provide calibrated predictions across a large set of protected groups. Multicalibration is known to be a distinct goal than loss minimization, even for simple…

Machine Learning · Computer Science 2023-12-11 Jarosław Błasiok , Parikshit Gopalan , Lunjia Hu , Adam Tauman Kalai , Preetum Nakkiran