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Related papers: Robust Voting under Uncertainty

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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

This work presents a new Distributionally Robust Optimization approach, using $p$-Wasserstein metrics, to analyze a stochastic program in a general context. The ambiguity set in this approach depends on the decision variable and is…

Optimization and Control · Mathematics 2023-03-08 Diego Fonseca , Mauricio Junca

In this paper we study several monotonicity axioms in approval-based multi-winner voting rules. We consider monotonicity with respect to the support received by the winners and also monotonicity in the size of the committee. Monotonicity…

Computer Science and Game Theory · Computer Science 2019-02-25 Luis Sánchez-Fernández , Jesús A. Fisteus

This paper considers structural optimization under a reliability constraint, where the input distribution is only partially known. Specifically, when we only know that the expected value vector and the variance-covariance matrix of the…

Optimization and Control · Mathematics 2022-12-19 Yoshihiro Kanno

In this paper, an optimization problem with uncertain constraint coefficients is considered. Possibility theory is used to model the uncertainty. Namely, a joint possibility distribution in constraint coefficient realizations, called…

Optimization and Control · Mathematics 2023-09-07 Romain Guillaume , Adam Kasperski , Pawel Zielinski

In recent years, there has been a growing interest in statistical methods that exhibit robust performance under distribution changes between training and test data. While most of the related research focuses on point predictions with the…

Methodology · Statistics 2024-06-18 Alexander Henzi , Xinwei Shen , Michael Law , Peter Bühlmann

The distributionally robust Markov Decision Process (MDP) approach asks for a distributionally robust policy that achieves the maximal expected total reward under the most adversarial distribution of uncertain parameters. In this paper, we…

Systems and Control · Computer Science 2018-10-10 Zhi Chen , Pengqian Yu , William B. Haskell

Voting is a very general method of preference aggregation. A voting rule takes as input every voter's vote (typically, a ranking of the alternatives), and produces as output either just the winning alternative or a ranking of the…

Computer Science and Game Theory · Computer Science 2012-07-09 Vincent Conitzer , Tuomas Sandholm

Consider an election between two candidates in which the voters' choices are random and independent and the probability of a voter choosing the first candidate is $p>1/2$. Condorcet's Jury Theorem which he derived from the weak law of large…

Probability · Mathematics 2007-05-23 Olle Haggstrom , Gil Kalai , Elchanan Mossel

Voting systems typically treat all voters equally. We argue that perhaps they should not: Voters who have supported good choices in the past should be given higher weight than voters who have supported bad ones. To develop a formal…

Computer Science and Game Theory · Computer Science 2017-03-16 Nika Haghtalab , Ritesh Noothigattu , Ariel D. Procaccia

It is well known that no reasonable voting rule is strategyproof. Moreover, the common Plurality rule is particularly prone to strategic behavior of the voters and empirical studies show that people often vote strategically in practice.…

Computer Science and Game Theory · Computer Science 2014-04-22 Reshef Meir , Omer Lev , Jeffrey S. Rosenschein

Uncertainties influencing the dynamical systems pose a significant challenge in estimating the achievable performance of a controller aiming to control such uncertain systems. When the uncertainties are of stochastic nature, obtaining hard…

Systems and Control · Electrical Eng. & Systems 2025-07-22 Venkatraman Renganathan

In this paper a class of optimization problems with uncertain linear constraints is discussed. It is assumed that the constraint coefficients are random vectors whose probability distributions are only partially known. Possibility theory is…

Optimization and Control · Mathematics 2021-11-30 Romain Guillaume , Adam Kasperski , Pawel Zielinski

We study notions of robustness of Markov kernels and probability distribution of a system that is described by $n$ input random variables and one output random variable. Markov kernels can be expanded in a series of potentials that allow to…

Commutative Algebra · Mathematics 2011-10-07 Johannes Rauh , Nihat Ay

Robustness of linear systems with constant coefficients is considered. There exist methods and tools for analyzing the stability of systems with random or deterministic uncertainties. At the same time, there are no approaches for the…

Optimization and Control · Mathematics 2020-12-08 Andrey Tremba

We investigate the problem of computing the probability of winning in an election where voter attendance is uncertain. More precisely, we study the setting where, in addition to a total ordering of the candidates, each voter is associated…

Computer Science and Game Theory · Computer Science 2021-02-01 Aviram Imber , Benny Kimelfeld

A policy is said to be robust if it maximizes the reward while considering a bad, or even adversarial, model. In this work we formalize two new criteria of robustness to action uncertainty. Specifically, we consider two scenarios in which…

Machine Learning · Computer Science 2019-05-08 Chen Tessler , Yonathan Efroni , Shie Mannor

Approval voting is widely used for making multi-winner voting decisions. The canonical rule (also called Approval Voting) used in the setting aims to maximize social welfare by selecting candidates with the highest number of approvals. We…

Computer Science and Game Theory · Computer Science 2026-04-21 Haris Aziz , Yuhang Guo , Venkateswara Rao Kagita , Baharak Rastegari , Mashbat Suzuki

We consider a data-driven robust hypothesis test where the optimal test will minimize the worst-case performance regarding distributions that are close to the empirical distributions with respect to the Wasserstein distance. This leads to a…

Statistics Theory · Mathematics 2021-06-01 Liyan Xie , Rui Gao , Yao Xie

When selecting a subset of candidates (a so-called committee) based on the preferences of voters, proportional representation is often a major desideratum. When going beyond simplistic models such as party-list or district-based elections,…

Computer Science and Game Theory · Computer Science 2023-02-07 Markus Brill , Jannik Peters