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We study a generalization of the standard approval-based model of participatory budgeting (PB), in which voters are providing approval ballots over a set of predefined projects and -- in addition to a global budget limit, there are several…

Computer Science and Game Theory · Computer Science 2020-12-10 Pallavi Jain , Krzysztof Sornat , Nimrod Talmon , Meirav Zehavi

We study the stationary states of variants of the noisy voter model, subject to fluctuating parameters or external environments. Specifically, we consider scenarios in which the herding-to-noise ratio switches randomly and on different time…

Physics and Society · Physics 2023-06-01 Annalisa Caligiuri , Tobias Galla

We introduce a non-linear variant of the voter model, the q-voter model, in which q neighbors (with possible repetition) are consulted for a voter to change opinion. If the q neighbors agree, the voter takes their opinion; if they do not…

Physics and Society · Physics 2009-11-27 C. Castellano , M. A. Munoz , R. Pastor-Satorras

We initiate the study of voting rules for participatory budgeting using the so-called epistemic approach, where one interprets votes as noisy reflections of some ground truth regarding the objectively best set of projects to fund. Using…

Computer Science and Game Theory · Computer Science 2024-09-05 Simon Rey , Ulle Endriss

Many segmentation tasks, such as medical image segmentation or future state prediction, are inherently ambiguous, meaning that multiple predictions are equally correct. Current methods typically rely on generative models to capture this…

Computer Vision and Pattern Recognition · Computer Science 2026-03-23 Sebastian Gerard , Josephine Sullivan

Social networks are increasingly being used to conduct polls. We introduce a simple model of such social polling. We suppose agents vote sequentially, but the order in which agents choose to vote is not necessarily fixed. We also suppose…

Computer Science and Game Theory · Computer Science 2013-02-08 Serge Gaspers , Victor Naroditskiy , Nina Narodytska , Toby Walsh

A restricted Boltzmann machine (RBM) learns a probability distribution over its input samples and has numerous uses like dimensionality reduction, classification and generative modeling. Conventional RBMs accept vectorized data that…

Computer Vision and Pattern Recognition · Computer Science 2018-11-13 Cong Chen , Kim Batselier , Ching-Yun Ko , Ngai Wong

A new feature selection method based on an improved maximal relevance and minimal redundancy (mRMR) criterion was proposed for power system transient stability assessment. First, the standard mRMR was improved by introducing a weight…

Signal Processing · Electrical Eng. & Systems 2019-03-06 Yang Li , Xueping Gu

In approval-based multiwinner voting, voters express approval preferences over a set of candidates, and the goal is to return a winning committee. This model captures a broad range of subset selection problems under preferences. Prior work…

Computer Science and Game Theory · Computer Science 2026-04-28 Niclas Boehmer , Luca Kreisel , Jannik Peters

Maximum likelihood estimation furnishes powerful insights into voting theory, and the design of voting rules. However the MLE can usually be badly corrupted by a single outlying sample. This means that a single voter or a group of colluding…

Data Structures and Algorithms · Computer Science 2022-07-19 Allen Liu , Ankur Moitra

Committee-selection problems arise in many contexts and applications, and there has been increasing interest within the social choice research community on identifying which properties are satisfied by different multi-winner voting rules.…

Artificial Intelligence · Computer Science 2025-08-11 Joshua Caiata , Ben Armstrong , Kate Larson

One of the fundamental structural properties of many networks is triangle closure. Whereas the influence of this transitivity on a variety of contagion dynamics has been previously explored, existing models of coevolving or adaptive network…

Adaptation and Self-Organizing Systems · Physics 2017-01-04 Nishant Malik , Feng Shi , Hsuan-Wei Lee , Peter J. Mucha

In this paper, we are concerned with how to select significant variables in semiparametric modeling. Variable selection for semiparametric regression models consists of two components: model selection for nonparametric components and…

Statistics Theory · Mathematics 2008-12-18 Runze Li , Hua Liang

There has been much recent work on multiwinner voting systems. However, sometimes a committee is highly structured, and if we want to vote for such a committee, our voting method should be more structured as well. We consider committees…

Computer Science and Game Theory · Computer Science 2022-11-14 Karl-Dieter Crisman

We design two mechanisms that ensure that the majority preferred option wins in all equilibria. The first one is a simultaneous game where agents choose other agents to cooperate with on top of the vote for an alternative, thus overcoming…

Theoretical Economics · Economics 2023-10-12 Kirneva Margarita , Núñez Matías

Support vector machines (SVMs) are widely used and constitute one of the best examined and used machine learning models for two-class classification. Classification in SVM is based on a score procedure, yielding a deterministic…

Machine Learning · Statistics 2023-10-11 Sandra Benítez-Peña , Rafael Blanquero , Emilio Carrizosa , Pepa Ramírez-Cobo

Ensuring safety is a critical requirement for autonomous systems, yet providing formal guarantees for nominal controllers remains a significant challenge. In this paper, we propose a modular sampling-based safety filter to ensure the safety…

Systems and Control · Electrical Eng. & Systems 2026-04-27 Junyoung Park , Hyeontae Sung , Heejin Ahn

Participatory budgeting engages the public in the process of allocating public money to different types of projects. PB designs differ in how voters are asked to express their preferences over candidate projects and how these preferences…

Computer Science and Game Theory · Computer Science 2023-02-28 Roy Fairstein , Gerdus Benadè , Kobi Gal

Stability Selection was recently introduced by Meinshausen and Buhlmann (2010) as a very general technique designed to improve the performance of a variable selection algorithm. It is based on aggregating the results of applying a selection…

Statistics Theory · Mathematics 2016-04-27 Rajen D. Shah , Richard J. Samworth

In this paper, we examine the concept of modularity, an often cited advantage of the ruled-based representation methodology. We argue that the notion of modularity consists of two distinct concepts which we call syntactic modularity and…

Artificial Intelligence · Computer Science 2013-04-12 David Heckerman , Eric J. Horvitz