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Related papers: Rank Aggregation Using Scoring Rules

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We investigate the parameterized complexity of strategic behaviors in generalized scoring rules. In particular, we prove that the manipulation, control (all the 22 standard types), and bribery problems are fixed-parameter tractable for most…

Computer Science and Game Theory · Computer Science 2014-05-27 Yongjie Yang

In this paper we introduce an iterative voting algorithm and then use it to obtain a rating method which is very robust against collusion attacks as well as random and biased raters. Unlike the previous iterative methods, our method is not…

Information Retrieval · Computer Science 2014-06-12 Mohammad Allahbakhsh , Aleksandar Ignjatovic

We characterise multi-candidate pure-strategy equilibria in the Hotelling-Downs spatial election model for the class of best-worst voting rules, in which each voter is endowed with both a positive and a negative vote, i.e., each voter can…

Computer Science and Game Theory · Computer Science 2016-10-11 Dodge Cahan , Arkadii Slinko

We study the {PAC} learnability of multiwinner voting, focusing on the class of approval-based committee scoring (ABCS) rules. These are voting rules applied on profiles with approval ballots, where each voter approves some of the…

Computer Science and Game Theory · Computer Science 2023-08-02 Ioannis Caragiannis , Karl Fehrs

Rank aggregation systems collect ordinal preferences from individuals to produce a global ranking that represents the social preference. Rank-breaking is a common practice to reduce the computational complexity of learning the global…

Machine Learning · Computer Science 2016-10-10 Ashish Khetan , Sewoong Oh

Ranked voting systems, such as instant-runoff voting (IRV) and single transferable vote (STV), are used in many places around the world. They are more complex than plurality and scoring rules, presenting a challenge for auditing their…

Evaluating performance across optimization algorithms on many problems presents a complex challenge due to the diversity of numerical scales involved. Traditional data processing methods, such as hypothesis testing and Bayesian inference,…

Optimization and Control · Mathematics 2024-09-10 Yunpeng Jinng , Qunfeng Liu

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

Approval-based committee (ABC) voting rules elect a fixed size subset of the candidates, a so-called committee, based on the voters' approval ballots over the candidates. While these rules have recently attracted significant attention,…

Computer Science and Game Theory · Computer Science 2023-02-24 Chris Dong , Patrick Lederer

We consider elections where the voters come one at a time, in a streaming fashion, and devise space-efficient algorithms which identify an approximate winning committee with respect to common multiwinner proportional representation voting…

Computer Science and Game Theory · Computer Science 2017-03-01 Palash Dey , Nimrod Talmon , Otniel van Handel

While proportionality is frequently named as a desirable property of voting rules, its interpretation in multiwinner voting differs significantly from that in apportionment. We aim to bridge these two distinct notions of proportionality by…

Computer Science and Game Theory · Computer Science 2026-02-11 Daria Boratyn , Dariusz Stolicki

To understand and summarize approval preferences and other binary evaluation data, it is useful to order the items on an axis which explains the data. In a political election using approval voting, this could be an ideological left-right…

Computer Science and Game Theory · Computer Science 2024-05-08 Théo Delemazure , Chris Dong , Dominik Peters , Magdaléna Tydrichová

Online learning to rank is a sequential decision-making problem where in each round the learning agent chooses a list of items and receives feedback in the form of clicks from the user. Many sample-efficient algorithms have been proposed…

Machine Learning · Statistics 2019-03-20 Tor Lattimore , Branislav Kveton , Shuai Li , Csaba Szepesvari

This paper considers the problem of inference after ranking. In our setting, we are interested in any population whose rank according to some random quantity, such as an estimated treatment effect, a measure of value-added, or benefit (net…

Econometrics · Economics 2026-01-06 Andreas Petrou-Zeniou , Azeem M. Shaikh

Ranking is used in sport leagues to determine a champion and/or to decide on promotion/relegation of teams. Arguably, the best known ranking method relies on scores obtained by cumulating the points associated with the wins and the draws of…

Physics and Society · Physics 2023-03-28 Leszek Szczecinski

State-of-the-art results in typical classification tasks are mostly achieved by unexplainable machine learning methods, like deep neural networks, for instance. Contrarily, in this paper, we investigate the application of rule learning…

Machine Learning · Computer Science 2024-03-11 Albert Nössig , Tobias Hell , Georg Moser

In social choice theory, (Kemeny) rank aggregation is a well-studied problem where the goal is to combine rankings from multiple voters into a single ranking on the same set of items. Since rankings can reveal preferences of voters (which a…

Data Structures and Algorithms · Computer Science 2021-12-30 Daniel Alabi , Badih Ghazi , Ravi Kumar , Pasin Manurangsi

The pairwise winning indices, computed in the Stochastic Multicriteria Acceptability Analysis, give the probability with which an alternative is preferred to another taking into account all the instances of the assumed preference model…

Optimization and Control · Mathematics 2022-03-29 Sally Giuseppe Arcidiacono , Salvatore Corrente , Salvatore Greco

We develop a model of multiwinner elections that combines performance-based measures of the quality of the committee (such as, e.g., Borda scores of the committee members) with diversity constraints. Specifically, we assume that the…

Computer Science and Game Theory · Computer Science 2017-11-23 Robert Bredereck , Piotr Faliszewski , Ayumi Igarashi , Martin Lackner , Piotr Skowron

We consider the problem of sequential evaluation, in which an evaluator observes candidates in a sequence and assigns scores to these candidates in an online, irrevocable fashion. Motivated by the psychology literature that has studied…

Machine Learning · Statistics 2023-11-20 Jingyan Wang , Ashwin Pananjady