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Given a graph $G$, a community structure $\mathcal{C}$, and a budget $k$, the fair influence maximization problem aims to select a seed set $S$ ($|S|\leq k$) that maximizes the influence spread while narrowing the influence gap between…

Data Structures and Algorithms · Computer Science 2023-11-23 Xiaobin Rui , Zhixiao Wang , Jiayu Zhao , Lichao Sun , Wei Chen

This is an expository paper on approximating functions from general Hilbert or Banach spaces in the worst case, average case and randomized settings with error measured in the $L_p$ sense. We define the power function as the ratio between…

Numerical Analysis · Mathematics 2011-06-08 Erich Novak , Henryk Woźniakowski

We are interested in ensemble methods to solve multi-objective optimization problems. An ensemble Kalman method is proposed to solve a formulation of the nonlinear problem using a weighted function approach. An analysis of the mean field…

Numerical Analysis · Mathematics 2022-03-21 Michael Herty , Elisa Iacomini

We develop a reverse entropy power inequality for convex measures, which may be seen as an affine-geometric inverse of the entropy power inequality of Shannon and Stam. The specialization of this inequality to log-concave measures may be…

Functional Analysis · Mathematics 2012-04-02 Sergey Bobkov , Mokshay Madiman

Recent advances in counter-adversarial systems have garnered significant research attention to inverse filtering from a Bayesian perspective. For example, interest in estimating the adversary's Kalman filter tracked estimate with the…

Optimization and Control · Mathematics 2023-08-15 Himali Singh , Arpan Chattopadhyay , Kumar Vijay Mishra

Probability distributions having power-law tails are observed in a broad range of social, economic, and biological systems. We describe here a potentially useful common framework. We derive distribution functions $\{p_k\}$ for situations in…

Physics and Society · Physics 2015-01-07 Jack Peterson , Purushottam D. Dixit , Ken A. Dill

A recently proposed graph-theoretic metric, the influence gap, has shown to be a reliable predictor of the effect of social influence in two-party elections, albeit only tested on regular and scale-free graphs. Here, we investigate whether…

Social and Information Networks · Computer Science 2022-02-09 Jacques Bara , Omer Lev , Paolo Turrini

The entropy power inequality, which plays a fundamental role in information theory and probability, may be seen as an analogue of the Brunn-Minkowski inequality. Motivated by this connection to Convex Geometry, we survey various recent…

Information Theory · Computer Science 2020-02-07 Mokshay Madiman , James Melbourne , Peng Xu

We study the problem of minimizing metric distortion in multi-winner elections, where a committee of size $k$ is selected from a set of candidates based on voters' ordinal preferences. We assume that voters and candidates are embedded on a…

Computer Science and Game Theory · Computer Science 2026-02-18 Negar Babashah , Hasti Karimi , Masoud Seddighin , Golnoosh Shahkarami

This paper uses a probabilistic approach to analyze the converge of an ensemble Kalman filter solution to an exact Kalman filter solution in the simplest possible setting, the scalar case, as it allows us to build upon a rich literature of…

Optimization and Control · Mathematics 2020-03-31 Andrey A Popov , Adrian Sandu

A proposed measure of voting power should satisfy two conditions to be plausible: first, it must be conceptually justified, capturing the intuitive meaning of what voting power is; second, it must satisfy reasonable postulates. This paper…

Theoretical Economics · Economics 2022-05-18 Arash Abizadeh , Adrian Vetta

In this paper, we study the problem of distributed estimation with an emphasis on communication-efficiency. The proposed algorithm is based on a windowed maximum a posteriori (MAP) estimation problem, wherein each agent in the network…

Robotics · Computer Science 2022-11-22 Miguel Calvo-Fullana , Jonathan P. How

This paper considers the problem of steering an arbitrary initial probability density function to an arbitrary terminal one, where the system dynamics is governed by a first-order linear stochastic difference equation. It is a…

Optimization and Control · Mathematics 2023-07-06 Guangyu Wu , Anders Lindquist

This work presents an approach to the inverse design of scattering systems by modifying the transmission matrix using reinforcement learning. We utilize Proximal Policy Optimization to navigate the highly non-convex landscape of the object…

Optics · Physics 2025-06-17 Yuhao Kang

We propose a stochastic map model of economic dynamics. In the last decade, an array of observations in economics has been investigated in the econophysics literature, a major example being the universal features of inequality in terms of…

General Finance · Quantitative Finance 2015-05-27 Anindya S. Chakrabarti

Using the Generalised Lotka Volterra (GLV) model adapted to deal with muti agent systems we can investigate economic systems from a general viewpoint and obtain generic features common to most economies. Assuming only weak generic…

Statistical Mechanics · Physics 2009-11-07 Sorin Solomon , Peter Richmond

Systems of indirect voting based on the principle of qualified majority can be analysed using the methods of game theory. In particular, this applies to the voting system in the Council of the European Union, which was recently a subject of…

Physics and Society · Physics 2007-05-23 Wojciech Slomczynski , Karol Zyczkowski

In this paper we address the problem of estimating the ratio $\frac{q}{p}$ where $p$ is a density function and $q$ is another density, or, more generally an arbitrary function. Knowing or approximating this ratio is needed in various…

Machine Learning · Computer Science 2013-04-26 Qichao Que , Mikhail Belkin

We consider the problem of computing ratings using the results of games played between a set of n players, and show how this problem can be reduced to computing the positive eigenvectors corresponding to the dominant eigenvalues of certain…

Numerical Analysis · Mathematics 2010-05-06 Richard P. Brent

In real-world recommender systems, user-item interactions are Missing Not At Random (MNAR), as interactions with popular items are more frequently observed than those with less popular ones. Missing observations shift recommendations toward…

Information Retrieval · Computer Science 2025-12-25 Kazuma Onishi , Katsuhiko Hayashi , Hidetaka Kamigaito