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A method is given for quantitatively rating the social acceptance of different options which are the matter of a preferential vote. The proposed method is proved to satisfy certain desirable conditions, among which there is a majority…

Optimization and Control · Mathematics 2009-12-12 Rosa Camps , Xavier Mora , Laia Saumell

A method is given for quantitatively rating the social acceptance of different options which are the matter of a preferential vote. In contrast to a previous article, here the individual votes are allowed to be incomplete, that is, they…

Optimization and Control · Mathematics 2012-03-09 Rosa Camps , Xavier Mora , Laia Saumell

A method is given for quantitatively rating the social acceptance of different options which are the matter of a complete preferential vote. Completeness means that every voter expresses a comparison (a preference or a tie) about each pair…

Optimization and Control · Mathematics 2012-03-09 Rosa Camps , Xavier Mora , Laia Saumell

Several rules for social choice are examined from a unifying point of view that looks at them as procedures for revising a system of degrees of belief in accordance with certain specified logical constraints. Belief is here a social…

Artificial Intelligence · Computer Science 2015-05-06 Rosa Camps , Xavier Mora , Laia Saumell

Understanding political phenomena requires measuring the political preferences of society. We introduce a model based on mixtures of spatial voting models that infers the underlying distribution of political preferences of voters with only…

Computers and Society · Computer Science 2016-10-27 Alison Nahm , Alex Pentland , Peter Krafft

The traditional social recommendation algorithm ignores the following fact: the preferences of users with trust relationships are not necessarily similar, and the consideration of user preference similarity should be limited to specific…

Information Retrieval · Computer Science 2019-03-13 Wei Peng , Baogui Xin

Feature selection can facilitate the learning of mixtures of discrete random variables as they arise, e.g. in crowdsourcing tasks. Intuitively, not all workers are equally reliable but, if the less reliable ones could be eliminated, then…

Machine Learning · Statistics 2017-11-28 Vincent Zhao , Steven W. Zucker

Fractional scoring has been proposed to avoid inconsistencies in the attribution of publications to percentile rank classes. Uncertainties and ambiguities in the evaluation of percentile ranks can be demonstrated most easily with small…

Digital Libraries · Computer Science 2013-03-25 Michael Schreiber

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 study the ranking of individuals, teams, or objects, based on pairwise comparisons between them, using the Bradley-Terry model. Estimates of rankings within this model are commonly made using a simple iterative algorithm first introduced…

Machine Learning · Statistics 2023-08-16 M. E. J. Newman

This paper investigates two feature-scoring criteria that make use of estimated class probabilities: one method proposed by \citet{shen} and a complementary approach proposed below. We develop a theoretical framework to analyze each…

Machine Learning · Computer Science 2012-07-03 Andrea Danyluk , Nicholas Arnosti

We study the problem of fair sequential decision making given voter preferences. In each round, a decision rule must choose a decision from a set of alternatives where each voter reports which of these alternatives they approve. Instead of…

Computer Science and Game Theory · Computer Science 2025-03-18 Nikhil Chandak , Shashwat Goel , Dominik Peters

When aggregating preferences of agents via voting, two desirable goals are to incentivize agents to participate in the voting process and then identify outcomes that are Pareto efficient. We consider participation as formalized by Brandl,…

Computer Science and Game Theory · Computer Science 2017-05-02 Haris Aziz , Pang Luo , Christine Rizkallah

Matrix factorization is a key component of collaborative filtering-based recommendation systems because it allows us to complete sparse user-by-item ratings matrices under a low-rank assumption that encodes the belief that similar users…

Machine Learning · Statistics 2016-04-22 Aleksandr Y. Aravkin , Kush R. Varshney , Liu Yang

With ever-increasing amounts of online information available, modeling and predicting individual preferences-for books or articles, for example-is becoming more and more important. Good predictions enable us to improve advice to users, and…

Social and Information Networks · Computer Science 2017-02-06 Antonia Godoy-Lorite , Roger Guimera , Cristopher Moore , Marta Sales-Pardo

We propose a topic modeling approach to the prediction of preferences in pairwise comparisons. We develop a new generative model for pairwise comparisons that accounts for multiple shared latent rankings that are prevalent in a population…

Machine Learning · Computer Science 2015-01-27 Weicong Ding , Prakash Ishwar , Venkatesh Saligrama

In this paper, we study the problem of Participatory Budgeting (PB) with approval ballots, inspired by Multi-Winner Voting schemes. We present generalized preference aggregation methods for participatory budgeting, especially for finding…

Computational Engineering, Finance, and Science · Computer Science 2024-10-10 Rutvik Page , Arnav Doifode , Jitendra Tembhurne , Aishwarya Sagar Anand Ukey

We propose a simple method for combining together voting rules that performs a run-off between the different winners of each voting rule. We prove that this combinator has several good properties. For instance, even if just one of the base…

Artificial Intelligence · Computer Science 2012-03-15 Nina Narodytska , Toby Walsh , Lirong Xia

Collaborative filtering is a very useful general technique for exploiting the preference patterns of a group of users to predict the utility of items to a particular user. Previous research has studied several probabilistic graphic models…

Information Retrieval · Computer Science 2012-12-12 Rong Jin , Luo Si , ChengXiang Zhai

In this paper we extend the principle of proportional representation to rankings. We consider the setting where alternatives need to be ranked based on approval preferences. In this setting, proportional representation requires that…

Computer Science and Game Theory · Computer Science 2016-12-06 Piotr Skowron , Martin Lackner , Markus Brill , Dominik Peters , Edith Elkind
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