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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 study electoral campaign management scenarios in which an external party can buy votes, i.e., pay the voters to promote its preferred candidate in their preference rankings. The external party's goal is to make its preferred candidate a…

Computer Science and Game Theory · Computer Science 2010-11-29 Edith Elkind , Piotr Faliszewski

Several multi-winner systems that use approval voting have been developed but they each suffer from various problems. Six of these methods are discussed in this paper. They are Satisfaction Approval Voting, Minimax Approval Voting,…

Computer Science and Game Theory · Computer Science 2016-03-17 Toby Pereira

Determining the complexity of election attack problems is a major research direction in the computational study of voting problems. The paper "Towards completing the puzzle: complexity of control by replacing, adding, and deleting…

Computer Science and Game Theory · Computer Science 2023-05-29 Zack Fitzsimmons , Edith Hemaspaandra

We consider the computational complexity of a problem modeling bribery in the context of voting systems. In the scenario of Swap Bribery, each voter assigns a certain price for swapping the positions of two consecutive candidates in his…

Computational Complexity · Computer Science 2015-05-20 Britta Dorn , Ildikó Schlotter

Motivated by the common academic problem of allocating papers to referees for conference reviewing we propose a novel mechanism for solving the assignment problem when we have a two sided matching problem with preferences from one side (the…

Artificial Intelligence · Computer Science 2017-05-22 Jing Wu Lian , Nicholas Mattei , Renee Noble , Toby Walsh

This paper presents a new solution for choosing the K parameter in the k-nearest neighbor (KNN) algorithm, the solution depending on the idea of ensemble learning, in which a weak KNN classifier is used each time with a different K,…

Machine Learning · Computer Science 2014-09-04 Ahmad Basheer Hassanat , Mohammad Ali Abbadi , Ghada Awad Altarawneh , Ahmad Ali Alhasanat

In the apportionment problem, a fixed number of seats must be distributed among parties in proportion to the number of voters supporting each party. We study a generalization of this setting, in which voters can support multiple parties by…

Computer Science and Game Theory · Computer Science 2022-03-31 Markus Brill , Paul Gölz , Dominik Peters , Ulrike Schmidt-Kraepelin , Kai Wilker

We present a new model that describes the process of electing a group of representatives (e.g., a parliament) for a group of voters. In this model, called the voting committee model, the elected group of representatives runs a number of…

Multiagent Systems · Computer Science 2016-11-22 Piotr Skowron

Election rules are formal processes that aggregate voters preferences, typically to select a single candidate, called the winner. Most of the election rules studied in the literature require the voters to rank the candidates from the most…

Data Structures and Algorithms · Computer Science 2019-01-31 Matthias Bentert , Piotr Skowron

Approval-like voting rules, such as Sincere-Strategy Preference-Based Approval voting (SP-AV), the Bucklin rule (an adaptive variant of $k$-Approval voting), and the Fallback rule (an adaptive variant of SP-AV) have many desirable…

Computer Science and Game Theory · Computer Science 2015-01-05 Ildikó Schlotter , Piotr Faliszewski , Edith Elkind

The recommendation system is a software system to predict customers' unknown preferences from known preferences. In the recommendation system, customers' preferences are encoded into vectors, and finding the nearest vectors to each vector…

Information Retrieval · Computer Science 2010-07-16 Kimikazu Kato , Tikara Hosino

We consider the problem of ranking $n$ experts according to their abilities, based on the correctness of their answers to $d$ questions. This is modeled by the so-called crowd-sourcing model, where the answer of expert $i$ on question $k$…

Statistics Theory · Mathematics 2025-12-25 Alexandra Carpentier , Nicolas Verzelen

We study strategic candidate positioning in multidimensional spatial-voting elections. Voters and candidates are represented as points in $\mathbb{R}^d$, and each voter supports the candidate that is closest under a distance induced by an…

Computer Science and Game Theory · Computer Science 2025-08-20 Colin Cleveland , Bart de Keijzer , Maria Polukarov

We study the problem of finding a small subset of items that is \emph{agreeable} to all agents, meaning that all agents value the subset at least as much as its complement. Previous work has shown worst-case bounds, over all instances with…

Computer Science and Game Theory · Computer Science 2019-02-06 Pasin Manurangsi , Warut Suksompong

Studying the computational complexity and designing fast algorithms for determining winners under voting rules are classical and fundamental questions in computational social choice. In this paper, we accelerate voting by leveraging quantum…

Computers and Society · Computer Science 2023-06-12 Ao Liu , Qishen Han , Lirong Xia , Nengkun Yu

We study the problem of fair $k$-committee selection under an egalitarian objective. Given $n$ agents partitioned into $m$ groups (\eg, demographic quotas), the goal is to aggregate their preferences to form a committee of size $k$ that…

Data Structures and Algorithms · Computer Science 2026-01-01 Ameet Gadekar , Aristides Gionis , Suhas Thejaswi , Sijing Tu

In this paper, we consider lightweight decentralised algorithms for achieving consensus in distributed systems. Each member of a distributed group has a private value from a fixed set consisting of, say, two elements, and the goal is for…

Probability · Mathematics 2013-11-20 James Cruise , Ayalvadi Ganesh

Team assembly is a problem that demands trade-offs between multiple fairness criteria and computational optimization. We focus on four criteria: (i) fair distribution of workloads within the team, (ii) fair distribution of skills and…

Databases · Computer Science 2023-06-27 Rodrigo Borges , Otto Sahlgrens , Sami Koivunen , Kostas Stefanidis , Thomas Olsson , Arto Laitinen

In this paper, we tackle the resolution of chance-constrained problems reformulated via Sample Average Approximation. The resulting data-driven deterministic reformulation takes the form of a large-scale mixed-integer program cursed with…

Optimization and Control · Mathematics 2023-06-27 Álvaro Porras , Concepción Domínguez , Juan M. Morales , Salvador Pineda
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