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This work proposes a view of probability as a relative measure rather than an absolute one. To demonstrate this concept, we focus on finite outcome spaces and develop three fundamental axioms that establish requirements for relative…

Machine Learning · Statistics 2023-05-30 Max Sklar

The Council of the European Union (EU) is one of the main decision-making bodies of the EU. A number of decisions require a qualified majority, the support of 55% of the member states (currently 15) that represent at least 65% of the total…

Physics and Society · Physics 2026-04-02 Dóra Gréta Petróczy , László Csató

Clustering ensemble, or consensus clustering, has emerged as a powerful tool for improving both the robustness and the stability of results from individual clustering methods. Weighted clustering ensemble arises naturally from clustering…

Computer Vision and Pattern Recognition · Computer Science 2021-12-14 Mimi Zhang

Decision procedures aggregating the preferences of multiple agents can produce cycles and hence outcomes which have been described heuristically as `chaotic'. We make this description precise by constructing an explicit dynamical system…

Statistical Mechanics · Physics 2009-10-31 David A. Meyer , Thad A. Brown

We investigate a class of weighted voting games for which weights are randomly distributed over the standard probability simplex. We provide close-formed formulae for the expectation and density of the distribution of weight of the $k$-th…

Computer Science and Game Theory · Computer Science 2022-02-11 Daria Boratyn , Werner Kirsch , Wojciech Słomczyński , Dariusz Stolicki , Karol Życzkowski

Robust model fitting is a fundamental problem in computer vision: used to pre-process raw data in the presence of outliers. Maximisation of Consensus (MaxCon) is one of the most popular robust criteria and widely used. Recently (Tennakoon…

Computer Vision and Pattern Recognition · Computer Science 2022-03-08 Erchuan Zhang , David Suter , Ruwan Tennakoon , Tat-Jun Chin , Alireza Bab-Hadiashar , Giang Truong , Syed Zulqarnain Gilani

Data Shapley provides a principled approach to data valuation and plays a crucial role in data-centric machine learning (ML) research. Data selection is considered a standard application of Data Shapley. However, its data selection…

Machine Learning · Computer Science 2024-05-08 Jiachen T. Wang , Tianji Yang , James Zou , Yongchan Kwon , Ruoxi Jia

A new game-theoretic approach for combining multiple classifiers is proposed. A short introduction in Game Theory and coalitions illustrate the way any collective decision scheme can be viewed as a competitive game of coalitions that are…

Computer Science and Game Theory · Computer Science 2015-02-10 Harris V. Georgiou

In this communication, we propose a tentative to set the fundamental problem of measuring process done by a large structure on a microsopic one. We consider the example of voting when an entire society tries to measure globally opinions of…

Physics and Society · Physics 2024-11-08 François Dubois

We study the complexity of the following problem: Given two weighted voting games G' and G'' that each contain a player p, in which of these games is p's power index value higher? We study this problem with respect to both the…

Computational Complexity · Computer Science 2008-01-31 Piotr Faliszewski , Lane A. Hemaspaandra

In this paper we propose a novel method to forecast the result of elections using only official results of previous ones. It is based on the voter model with stubborn nodes and uses theoretical results developed in a previous work of ours.…

Social and Information Networks · Computer Science 2021-10-13 Antoine Vendeville , Benjamin Guedj , Shi Zhou

In this paper, we consider lightweight decentralised algorithms for achieving consensus in distributed systems. Each member of a distributed group has a private value from a fixed set consisting of, say, two elements, and the goal is for…

Probability · Mathematics 2013-11-20 James Cruise , Ayalvadi Ganesh

Starting with a set of weighted items, we want to create a generic sample of a certain size that we can later use to estimate the total weight of arbitrary subsets. For this purpose, we propose priority sampling which tested on Internet…

Data Structures and Algorithms · Computer Science 2007-05-23 Nick Duffield , Carsten Lund , Mikkel Thorup

The Shapley value is a game-theoretic notion for wealth distribution that is nowadays extensively used to explain complex data-intensive computation, for instance, in network analysis or machine learning. Recent theoretical works show that…

Databases · Computer Science 2022-01-04 Daniel Deutch , Nave Frost , Benny Kimelfeld , Mikaël Monet

We present a model for quantitatively identifying swing voters in congressional elections. This is achieved by predicting an individual voter's likelihood to vote and an individual voter's likelihood to vote for a given party, if he votes.…

Physics and Society · Physics 2014-05-21 Steven Ambadjes

Two indicators are classically used to evaluate the quality of rule-based classification systems: predictive accuracy, i.e. the system's ability to successfully reproduce learning data and coverage, i.e. the proportion of possible cases for…

Artificial Intelligence · Computer Science 2020-04-07 Nassim Dehouche

Abstraction and realization are bilateral processes that are key in deriving intelligence and creativity. In many domains, the two processes are approached through rules: high-level principles that reveal invariances within similar yet…

Machine Learning · Computer Science 2018-03-13 Haizi Yu , Tianxi Li , Lav R. Varshney

Weighted voting games are ubiquitous mathematical models which are used in economics, political science, neuroscience, threshold logic, reliability theory and distributed systems. They model situations where agents with variable voting…

Computer Science and Game Theory · Computer Science 2010-02-02 Haris Aziz , Mike Paterson

The power of multiple testing procedures can be increased by using weighted p-values (Genovese, Roeder and Wasserman 2005). We derive the optimal weights and we show that the power is remarkably robust to misspecification of these weights.…

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

This paper proposes a novel approach to explain the predictions made by data-driven methods. Since such predictions rely heavily on the data used for training, explanations that convey information about how the training data affects the…

Machine Learning · Statistics 2022-12-09 Andreas Brandsæter , Ingrid K. Glad
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