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Related papers: Approximating power by weights

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We study the inverse power index problem for weighted voting games: the problem of finding a weighted voting game in which the power of the players is as close as possible to a certain target distribution. Our goal is to find algorithms…

Computer Science and Game Theory · Computer Science 2013-07-02 Bart de Keijzer , Tomas B. Klos , Yingqian Zhang

Social studies researchers use graphs to model group activities in social networks. An important property in this context is the centrality of a vertex: the inverse of the average distance to each other vertex. We describe a randomized…

Data Structures and Algorithms · Computer Science 2011-03-08 David Eppstein , Joseph Wang

Election rules are formal processes that aggregate voters preferences, typically to select a single candidate, called the winner. Most of the election rules studied in the literature require the voters to rank the candidates from the most…

Data Structures and Algorithms · Computer Science 2019-01-31 Matthias Bentert , Piotr Skowron

In this paper, we obtain error bound for binomial and negative binomial approximations to weighted sums of locally dependent random variables, using Stein's method. We also discuss approximation results for weighted sums of independent…

Probability · Mathematics 2020-10-20 Amit N. Kumar

Power-law distributions are typical macroscopic features occurring in almost all complex systems observable in nature. As a result, researchers in quantitative analyses must often generate random synthetic variates obeying power-law…

Physics and Society · Physics 2014-11-11 Filippo Radicchi

We study sufficient conditions on weight functions under which norm approximations by analytic polynomials are possible. The weights we study include radial, non-radial, and angular weights.

Functional Analysis · Mathematics 2022-02-09 Ali Abkar

The ratio between the probability that two distributions $R$ and $P$ give to points $x$ are known as importance weights or propensity scores and play a fundamental role in many different fields, most notably, statistics and machine…

Machine Learning · Computer Science 2021-03-11 Parikshit Gopalan , Omer Reingold , Vatsal Sharan , Udi Wieder

The problem of extrapolating the series in powers of small variables to the region of large variables is addressed. Such a problem is typical of quantum theory and statistical physics. A method of extrapolation is developed based on…

Statistical Mechanics · Physics 2009-11-10 V. I. Yukalov , S. Gluzman

It is known that increasing powers of a continuous random variable converge in distribution to Benford's law as the exponent approaches infinity. The rate of convergence has been estimated using Fourier analysis, but we present an…

Probability · Mathematics 2013-07-23 Michał Ryszard Wójcik

Consensus about the universality of the power law feature in complex networks is experiencing profound challenges. To shine fresh light on this controversy, we propose a generic theoretical framework in order to examine the power law…

Physics and Society · Physics 2021-05-24 Xiaojun Zhang , Zheng He , Liwei Zhang , Lez Rayman-Bacchus , Yue Xiao , Shuhui Shen

We analyze from a theoretical point of view the impact of various approximations on W mass distributions. This is done both at parton level and after a simulated W mass reconstruction using constrained fits. The results may help to…

High Energy Physics - Phenomenology · Physics 2009-10-30 Alessandro Ballestrero , Roberto Chierici

The concept and technics of real space renormalization group are applied to study majority rule voting in hierarchical structures. It is found that democratic voting can lead to totalitarianism by keeping in power a small minority.…

Disordered Systems and Neural Networks · Physics 2009-10-31 Serge Galam

We consider the power to reject false values of the parameter in Frequentist methods for the calculation of confidence intervals. We connect the power with the physical significance (reliability) of confidence intervals for a parameter…

High Energy Physics - Experiment · Physics 2010-12-23 C. Giunti , M. Laveder

A key to causal inference with observational data is achieving balance in predictive features associated with each treatment type. Recent literature has explored representation learning to achieve this goal. In this work, we discuss the…

Machine Learning · Statistics 2021-02-25 Serge Assaad , Shuxi Zeng , Chenyang Tao , Shounak Datta , Nikhil Mehta , Ricardo Henao , Fan Li , Lawrence Carin

This paper is concerned with the asymptotic behavior of sums of terms which are a test function f evaluated at successive increments of a discretely sampled semimartingale. Typically the test function is a power function (when the power is…

Probability · Mathematics 2007-05-23 Jean Jacod

There has been some confusion concerning the animal group-size: an exponential distribution was deduced by maximizing the entropy; lognormal distributions were practically used; a power-law decay with exponent {3/2} was proposed in physical…

Statistical Mechanics · Physics 2007-05-23 Hiro-Sato Niwa

Weighting methods are widely used to adjust for covariates in observational studies, sample surveys, and regression settings. In this paper, we study a class of recently proposed weighting methods which find the weights of minimum…

Methodology · Statistics 2019-10-29 Yixin Wang , José R. Zubizarreta

We study a family of distance functions on rankings that allow for asymmetric treatments of alternatives and consider the distinct relevance of the top and bottom positions for ordered lists. We provide a full axiomatic characterization of…

Computer Science and Game Theory · Computer Science 2024-03-28 Andrea Aveni , Ludovico Crippa , Giulio Principi

In multiwinner approval voting, the goal is to select $k$-member committees based on voters' approval ballots. A well-studied concept of proportionality in this context is the justified representation (JR) axiom, which demands that no large…

Computer Science and Game Theory · Computer Science 2024-09-10 Edith Elkind , Piotr Faliszewski , Ayumi Igarashi , Pasin Manurangsi , Ulrike Schmidt-Kraepelin , Warut Suksompong

Influence diagrams allow for intuitive and yet precise description of complex situations involving decision making under uncertainty. Unfortunately, most of the problems described by influence diagrams are hard to solve. In this paper we…

Artificial Intelligence · Computer Science 2012-10-19 Denis D. Maua , Cassio Polpo de Campos , Marco Zaffalon
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