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Related papers: Weighted Voting Via No-Regret Learning

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A method is given for quantitatively rating the social acceptance of different options which are the matter of a preferential vote. In contrast to a previous article, here the individual votes are allowed to be incomplete, that is, they…

Optimization and Control · Mathematics 2012-03-09 Rosa Camps , Xavier Mora , Laia Saumell

A voting rule decides on a probability distribution over a set of m alternatives, based on rankings of those alternatives provided by agents. We assume that agents have cardinal utility functions over the alternatives, but voting rules have…

Computer Science and Game Theory · Computer Science 2024-01-23 Soroush Ebadian , Anson Kahng , Dominik Peters , Nisarg Shah

We argue that many general evaluation problems can be viewed through the lens of voting theory. Each task is interpreted as a separate voter, which requires only ordinal rankings or pairwise comparisons of agents to produce an overall…

Artificial Intelligence · Computer Science 2025-07-01 Marc Lanctot , Kate Larson , Yoram Bachrach , Luke Marris , Zun Li , Avishkar Bhoopchand , Thomas Anthony , Brian Tanner , Anna Koop

We study a problem where a group of agents has to decide how some fixed value should be shared among them. We are interested in settings where the share that each agent receives is based on how that agent is evaluated by other members of…

Computer Science and Game Theory · Computer Science 2013-06-04 Arthur Carvalho , Kate Larson

In a voting problem with a finite set of alternatives to choose from, we study the manipulation of tops-only rules. Since all non-dictatorial (onto) voting rules are manipulable when there are more than two alternatives and all preferences…

Theoretical Economics · Economics 2022-10-24 R. Pablo Arribillaga , Agustin G. Bonifacio

Many decision problems cannot be solved exactly and use several estimation algorithms that assign scores to the different available options. The estimation errors can have various correlations, from low (e.g. between two very different…

Machine Learning · Computer Science 2023-09-06 Theo Delemazure , François Durand , Fabien Mathieu

We present a new approach to the problems of evaluating and learning personalized decision policies from observational data of past contexts, decisions, and outcomes. Only the outcome of the enacted decision is available and the historical…

Machine Learning · Statistics 2019-06-04 Nathan Kallus

While the importance of personalized policymaking is widely recognized, fully personalized implementation remains rare in practice, often due to legal, fairness or cost concerns. We study the problem of policy targeting for a regret-averse…

Econometrics · Economics 2026-04-07 Toru Kitagawa , Sokbae Lee , Chen Qiu

Covariate balance is crucial for unconfounded descriptive or causal comparisons. However, lack of balance is common in observational studies. This article considers weighting strategies for balancing covariates. We define a general class of…

Methodology · Statistics 2016-09-30 Fan Li , Kari Lock Morgan , Alan M. Zaslavsky

Covariate balance is crucial for unconfounded descriptive or causal comparisons. However, lack of balance is common in observational studies. This article considers weighting strategies for balancing covariates. We define a general class of…

Methodology · Statistics 2016-11-17 Fan Li , Kari Lock Morgan , Alan M. Zaslavsky

We consider the approval-based model of elections, and undertake a computational study of voting rules which select committees whose size is not predetermined. While voting rules that output committees with a predetermined number of winning…

Computer Science and Game Theory · Computer Science 2017-11-20 Piotr Faliszewski , Arkadii Slinko , Nimrod Talmon

In recent years, enlargement of the European Union has led to increased interest in the allocation of voting weights to member states with hugely differing population numbers. While the eventually agreed voting scheme lacks any strict…

General Mathematics · Mathematics 2008-09-11 Martin Kurth

Genome-wide association analysis has generated much discussion about how to preserve power to detect signals despite the detrimental effect of multiple testing on power. We develop a weighted multiple testing procedure that facilitates the…

Statistics Theory · Mathematics 2007-06-13 Kathryn Roeder , Bernie Devlin , Larry Wasserman

Given that conventional recommenders, while deeply effective, rely on large distributed systems pre-trained on aggregate user data, incorporating new data necessitates large training cycles, making them slow to adapt to real-time user…

Information Retrieval · Computer Science 2025-11-11 Rafayel Latif , Satwik Behera , Ali Al-Ebrahim

When predicting future events, it is common to issue forecasts that are probabilistic, in the form of probability distributions over the range of possible outcomes. Such forecasts can be evaluated using proper scoring rules. Proper scoring…

Computation · Statistics 2023-05-15 Sam Allen

A proposal in a weighted voting game is accepted if the sum of the (non-negative) weights of the "yea" voters is at least as large as a given quota. Several authors have considered representations of weighted voting games with minimum sum,…

Combinatorics · Mathematics 2018-05-03 Sascha Kurz

We discuss weighted scoring rules for forecast evaluation and their connection to hypothesis testing. First, a general construction principle for strictly locally proper weighted scoring rules based on conditional densities and scoring…

Methodology · Statistics 2017-01-12 Hajo Holzmann , Bernhard Klar

Most analyses of manipulation of voting schemes have adopted two assumptions that greatly diminish their practical import. First, it is usually assumed that the manipulators have full knowledge of the votes of the nonmanipulating agents.…

Computer Science and Game Theory · Computer Science 2012-10-19 Tyler Lu , Pingzhong Tang , Ariel D. Procaccia , Craig Boutilier

In this paper we consider the possibility of computing rather than training the decision layer weights of a neural classifier. Such a possibility arises in two way, from making an appropriate choice of loss function and by solving a problem…

Machine Learning · Computer Science 2022-09-21 Eugene Wong

We study the Shapley value in weighted voting games. The Shapley value has been used as an index for measuring the power of individual agents in decision-making bodies and political organizations, where decisions are made by a majority vote…

Computer Science and Game Theory · Computer Science 2014-08-05 Joel Oren , Yuval Filmus , Yair Zick , Yoram Bachrach
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