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Related papers: Approval-Based Committee Voting under Uncertainty

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In this work, we consider a school choice scenario where a student does not exactly know which college is better for her. Although it is hard for a student to obtain an exact preference, she can usually compare specific features of…

Computer Science and Game Theory · Computer Science 2026-02-16 Yao Zhang , Makoto Yokoo

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

Estimating the unknown number of classes in a population has numerous important applications. In a Poisson mixture model, the problem is reduced to estimating the odds that a class is undetected in a sample. The discontinuity of the odds…

Statistics Theory · Mathematics 2007-08-22 Chang Xuan Mao , Bruce G. Lindsay

We propose a new approach for solving a class of discrete decision making problems under uncertainty with positive cost. This issue concerns multiple and diverse fields such as engineering, economics, artificial intelligence, cognitive…

Artificial Intelligence · Computer Science 2014-01-03 Steve N'Guyen , Clément Moulin-Frier , Jacques Droulez

In party-approval multiwinner elections the goal is to allocate the seats of a fixed-size committee to parties based on the approval ballots of the voters over the parties. In particular, each voter can approve multiple parties and each…

Computer Science and Game Theory · Computer Science 2022-11-28 Théo Delemazure , Tom Demeulemeester , Manuel Eberl , Jonas Israel , Patrick Lederer

Multi-winner voting rules based on approval ballots have received increased attention in recent years. In particular Satisfaction Approval Voting (SAV) and its variants have been proposed. In this note, we show that the winning set can be…

Computer Science and Game Theory · Computer Science 2015-01-12 Haris Aziz , Toby Walsh

Various strategies for active learning have been proposed in the machine learning literature. In uncertainty sampling, which is among the most popular approaches, the active learner sequentially queries the label of those instances for…

Machine Learning · Computer Science 2019-09-04 Vu-Linh Nguyen , Sébastien Destercke , Eyke Hüllermeier

I study the optimal voting mechanism for a committee that must decide whether to enact or block a policy of unknown benefit. Information can come both from committee members who can acquire it at cost, and a strategic lobbyist who wishes…

Theoretical Economics · Economics 2025-08-04 D. Carlos Akkar

Various structured argumentation frameworks utilize preferences as part of their standard inference procedure to enable reasoning with preferences. In this paper, we consider an inverse of the standard reasoning problem, seeking to identify…

Artificial Intelligence · Computer Science 2020-05-13 Quratul-ain Mahesar , Nir Oren , Wamberto W. Vasconcelos

In the context of computational social choice, we study voting methods that assign a set of winners to each profile of voter preferences. A voting method satisfies the property of positive involvement (PI) if for any election in which a…

Computer Science and Game Theory · Computer Science 2021-06-23 Wesley H. Holliday , Eric Pacuit

Epistemic voting interprets votes as noisy signals about a ground truth. We consider contexts where the truth consists of a set of objective winners, knowing a lower and upper bound on its cardinality. A prototypical problem for this…

Artificial Intelligence · Computer Science 2022-01-19 Tahar Allouche , Jérôme Lang , Florian Yger

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

The traditional axiomatic approach to voting is motivated by the problem of reconciling differences in subjective preferences. In contrast, a dominant line of work in the theory of voting over the past 15 years has considered a different…

Discrete Mathematics · Computer Science 2015-12-19 Flavio Chierichetti , Jon Kleinberg

We study settings in which agents with incomplete preferences need to make a collective decision. We focus on a process of majority dynamics where issues are addressed one at a time and undecided agents follow the opinion of the majority.…

Computer Science and Game Theory · Computer Science 2022-05-03 Sirin Botan , Simon Rey , Zoi Terzopoulou

This paper studies a class of consensus dynamics where the interactions between agents are affected by a time-varying unknown scaling factor. This situation is encountered in the control of robotic fleets over a wireless network or in…

Systems and Control · Electrical Eng. & Systems 2025-11-14 Zoltan Nagy , Irinel-Constantin Morarescu , Lucian Busoniu

We consider methods for aggregating preferences that are based on the resolution of discrete optimization problems. The preferences are represented by arbitrary binary relations (possibly weighted) or incomplete paired comparison matrices.…

Optimization and Control · Mathematics 2007-05-23 Pavel Chebotarev , Elena Shamis

Design-based frameworks of uncertainty are frequently used in settings where the treatment is (conditionally) randomly assigned. This paper develops a design-based framework suitable for analyzing quasi-experimental settings in the social…

Econometrics · Economics 2025-06-17 Ashesh Rambachan , Jonathan Roth

Participatory Budgeting (PB) is commonly studied from an axiomatic perspective, where the aim is to design procedurally fair and economically efficient rules for voters with full information regarding their preferences. In contrast, we take…

Computer Science and Game Theory · Computer Science 2026-01-28 Qishen Han , Artem Ivaniuk , Edith Elkind , Lirong Xia

We derive axiomatically the probability function that should be used to make decisions given any form of underlying uncertainty.

Artificial Intelligence · Computer Science 2013-04-08 Philippe Smets

Recommender systems are personalized: we expect the results given to a particular user to reflect that user's preferences. Some researchers have studied the notion of calibration, how well recommendations match users' stated preferences,…

Information Retrieval · Computer Science 2019-09-17 Kun Lin , Nasim Sonboli , Bamshad Mobasher , Robin Burke
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