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We study the problem of {\em impartial selection}, a topic that lies at the intersection of computational social choice and mechanism design. The goal is to select the most popular individual among a set of community members. The input can…

Computer Science and Game Theory · Computer Science 2021-02-19 Ioannis Caragiannis , George Christodoulou , Nicos Protopapas

We examine an approval-based model of Liquid Democracy with a budget constraint on voting and delegating costs, aiming to centrally select casting voters ensuring complete representation of the electorate. From a computational complexity…

Computer Science and Game Theory · Computer Science 2025-02-05 Shiri Alouf-Heffetz , Łukasz Janeczko , Grzegorz Lisowski , Georgios Papasotiropoulos

Predictive parity (PP), also known as sufficiency, is a core definition of algorithmic fairness essentially stating that model outputs must have the same interpretation of expected outcomes regardless of group. Testing and satisfying PP is…

Methodology · Statistics 2023-06-01 Cyrus DiCiccio , Brian Hsu , YinYin Yu , Preetam Nandy , Kinjal Basu

Sortition is the practice of delegating public decision-making to randomly selected panels. Recently, it has gained momentum worldwide through its use in citizens' assemblies, sparking growing interest within the computer science community.…

Computer Science and Game Theory · Computer Science 2025-05-20 Johannes Brustle , Simone Fioravanti , Tomasz Ponitka , Jeremy Vollen

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

Approximate Bayesian computation (ABC) is a popular likelihood-free inference method for models with intractable likelihood functions. As ABC methods usually rely on comparing summary statistics of observed and simulated data, the choice of…

Machine Learning · Statistics 2022-06-22 Ayush Bharti , Louis Filstroff , Samuel Kaski

Citizens' assemblies need to represent subpopulations according to their proportions in the general population. These large committees are often constructed in an online fashion by contacting people, asking for the demographic features of…

Artificial Intelligence · Computer Science 2021-12-06 Virginie Do , Jamal Atif , Jérôme Lang , Nicolas Usunier

Given a set of items and a set of evaluators who all individually rank them, how do we aggregate these evaluations into a single societal ranking? Work in social choice and statistics has produced many aggregation methods for this problem,…

Computer Science and Game Theory · Computer Science 2025-08-26 Ratip Emin Berker , Ben Armstrong , Vincent Conitzer , Nihar B. Shah

Human feedback is increasingly used across diverse applications like training AI models, developing recommender systems, and measuring public opinion -- with granular feedback often being preferred over binary feedback for its greater…

Machine Learning · Computer Science 2025-07-17 Anmol Kagrecha , Henrik Marklund , Potsawee Manakul , Richard Zeckhauser , Benjamin Van Roy

Approval voting is a common method of preference aggregation where voters vote by ``approving'' of a subset of candidates and the winner(s) are those who are approved of by the largest number of voters. In approval voting, the degree to…

Computer Science and Game Theory · Computer Science 2023-07-19 Hari Sarang Nathan

The mathematical study of voting, social choice theory, has traditionally only been applicable to choices among a few predetermined alternatives, but not to open-ended decisions such as collectively selecting a textual statement. We…

Computer Science and Game Theory · Computer Science 2025-03-07 Sara Fish , Paul Gölz , David C. Parkes , Ariel D. Procaccia , Gili Rusak , Itai Shapira , Manuel Wüthrich

This paper focuses on managing the cost of deliberation before action. In many problems, the overall quality of the solution reflects costs incurred and resources consumed in deliberation as well as the cost and benefit of execution, when…

Artificial Intelligence · Computer Science 2013-04-05 David Einav , Michael R. Fehling

Bayesian optimization (BO) has emerged during the last few years as an effective approach to optimizing black-box functions where direct queries of the objective are expensive. In this paper we consider the case where direct access to the…

Machine Learning · Statistics 2017-04-13 Javier Gonzalez , Zhenwen Dai , Andreas Damianou , Neil D. Lawrence

Preference elicitation is the task of suggesting a highly preferred configuration to a decision maker. The preferences are typically learned by querying the user for choice feedback over pairs or sets of objects. In its constructive…

Artificial Intelligence · Computer Science 2018-05-08 Paolo Dragone , Stefano Teso , Andrea Passerini

A central feature of many deliberative processes, such as citizens' assemblies and deliberative polls, is the opportunity for participants to engage directly with experts. While participants are typically invited to propose questions for…

Artificial Intelligence · Computer Science 2026-04-28 Soham De , Lodewijk Gelauff , Ashish Goel , Smitha Milli , Ariel Procaccia , Alice Siu

Public sector agencies perform the critical task of implementing the redistributive role of the State by acting as the leading provider of critical public services that many rely on. In recent years, public agencies have been increasingly…

Human-Computer Interaction · Computer Science 2026-05-06 Erina Seh-Young Moon , Shion Guha

What role do non-elected bureaucrats play when elections provide imperfect accountability and create incentives for pandering? We develop a model where politicians and bureaucrats interact to implement policy. Both can either be good,…

General Economics · Economics 2025-10-03 Simon Lodato , Christos Mavridis , Federico Vaccari

Iterative voting is a natural model of repeated strategic decision-making in social choice theory when agents have the opportunity to update their votes prior to finalizing the group decision. Prior work has analyzed the efficacy of…

Computer Science and Game Theory · Computer Science 2025-06-12 Joshua Kavner , Lirong Xia

Collaborative filtering is a useful technique for exploiting the preference patterns of a group of users to predict the utility of items for the active user. In general, the performance of collaborative filtering depends on the number of…

Machine Learning · Computer Science 2012-07-19 Rong Jin , Luo Si

This paper investigates mechanisms for scaling participation in participatory design (PD). Specifically, the paper focuses on managed communities, one strategy of generification work. We first give a brief introduction on the issue of…

Computers and Society · Computer Science 2020-05-29 Stefan Hochwarter , Babak A. Farshchian
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