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Related papers: Proportional Representation in Rank Aggregation

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This paper studies the allocation of voting weights in a committee representing groups of different sizes. We introduce a partial ordering of weight allocations based on stochastic comparison of social welfare. We show that when the number…

Theoretical Economics · Economics 2024-03-07 Kazuya Kikuchi

Student placements under diversity constraints are a common practice globally. This paper addresses the selection of students by a single school under a \emph{one-to-one convention}, where students can belong to multiple types but are…

Computer Science and Game Theory · Computer Science 2024-12-19 Zhaohong Sun , Makoto Yokoo

Rankings on online platforms help their end-users find the relevant information -- people, news, media, and products -- quickly. Fair ranking tasks, which ask to rank a set of items to maximize utility subject to satisfying group-fairness…

Computers and Society · Computer Science 2023-06-22 Sruthi Gorantla , Anay Mehrotra , Amit Deshpande , Anand Louis

We study a participatory budgeting problem of aggregating the preferences of agents and dividing a budget over the projects. A budget division solution is a probability distribution over the projects. The main purpose of our study concerns…

Computer Science and Game Theory · Computer Science 2020-11-02 Zhongzheng Tang , Chenhao Wang , Mengqi Zhang

In the past few years, there has been much work on incorporating fairness requirements into algorithmic rankers, with contributions coming from the data management, algorithms, information retrieval, and recommender systems communities. In…

Information Retrieval · Computer Science 2022-08-15 Meike Zehlike , Ke Yang , Julia Stoyanovich

A committee's decisions on more than two alternatives much depend on the adopted voting method, and so does the distribution of power among the committee members. We investigate how different aggregation methods such as plurality runoff,…

Computer Science and Game Theory · Computer Science 2021-02-15 Sascha Kurz , Alexander Mayer , Stefan Napel

Fair ranking problems arise in many decision-making processes that often necessitate a trade-off between accuracy and fairness. Many existing studies have proposed correction methods such as adding fairness constraints to a ranking model's…

Machine Learning · Computer Science 2022-04-26 Ryosuke Sonoda

Building fair recommender systems is a challenging and crucial area of study due to its immense impact on society. We extended the definitions of two commonly accepted notions of fairness to recommender systems, namely equality of…

Machine Learning · Statistics 2022-08-12 Preetam Nandy , Cyrus Diciccio , Divya Venugopalan , Heloise Logan , Kinjal Basu , Noureddine El Karoui

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 study budget aggregation under $\ell_1$-utilities, a model for collective decision making in which agents with heterogeneous preferences must allocate a public budget across a set of alternatives. Each agent reports their preferred…

Computer Science and Game Theory · Computer Science 2026-02-27 Javier Cembrano , Rupert Freeman , Ulrike Schmidt-Kraepelin , Markus Utke

We study the problem of coalitional manipulation---where $k$ manipulators try to manipulate an election on $m$ candidates---under general scoring rules, with a focus on the Borda protocol. We do so both in the weighted and unweighted…

Data Structures and Algorithms · Computer Science 2017-08-17 Orgad Keller , Avinatan Hassidim , Noam Hazon

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

Matching platforms, such as online dating services and job recommendations, have become increasingly prevalent. For the success of these platforms, it is crucial to design reciprocal recommender systems (RRSs) that not only increase the…

Information Retrieval · Computer Science 2026-02-26 Yoji Tomita , Tomohiko Yokoyama

Fair consensus building combines the preferences of multiple rankers into a single consensus ranking, while ensuring any group defined by a protected attribute (such as race or gender) is not disadvantaged compared to other groups. Manually…

Human-Computer Interaction · Computer Science 2022-08-03 Hilson Shrestha , Kathleen Cachel , Mallak Alkhathlan , Elke Rundensteiner , Lane Harrison

A new game-theoretic approach for combining multiple classifiers is proposed. A short introduction in Game Theory and coalitions illustrate the way any collective decision scheme can be viewed as a competitive game of coalitions that are…

Computer Science and Game Theory · Computer Science 2015-02-10 Harris V. Georgiou

Apportionment is the task of assigning resources to entities with different entitlements in a fair manner, and specifically a manner that is as proportional as possible. The best-known application is the assignment of parliamentary seats to…

Computer Science and Game Theory · Computer Science 2025-10-14 Julian Chingoma , Ulle Endriss , Ronald de Haan , Adrian Haret , Jan Maly

While conventional ranking systems focus solely on maximizing the utility of the ranked items to users, fairness-aware ranking systems additionally try to balance the exposure for different protected attributes such as gender or race. To…

Machine Learning · Computer Science 2021-12-14 Omid Memarrast , Ashkan Rezaei , Rizal Fathony , Brian Ziebart

A natural notion of rationality/consistency for aggregating models is that, for all (possibly aggregated) models $A$ and $B$, if the output of model $A$ is $f(A)$ and if the output model $B$ is $f(B)$, then the output of the model obtained…

Theoretical Economics · Economics 2021-12-13 Hamed Hamze Bajgiran , Houman Owhadi

Ranking algorithms are deployed widely to order a set of items in applications such as search engines, news feeds, and recommendation systems. Recent studies, however, have shown that, left unchecked, the output of ranking algorithms can…

Data Structures and Algorithms · Computer Science 2018-07-31 L. Elisa Celis , Damian Straszak , Nisheeth K. Vishnoi

Rankings are ubiquitous in the online world today. As we have transitioned from finding books in libraries to ranking products, jobs, job applicants, opinions and potential romantic partners, there is a substantial precedent that ranking…

Information Retrieval · Computer Science 2018-10-18 Ashudeep Singh , Thorsten Joachims