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Mutual information (MI) is a fundamental measure of statistical dependence between two variables, yet accurate estimation from finite data remains notoriously difficult. No estimator is universally reliable, and common approaches fail in…

Data Analysis, Statistics and Probability · Physics 2025-10-02 Eslam Abdelaleem , K. Michael Martini , Ilya Nemenman

We study learning dynamics induced by strategic agents who repeatedly play a game with an unknown payoff-relevant parameter. In each step, an information system estimates a belief distribution of the parameter based on the players'…

Systems and Control · Electrical Eng. & Systems 2020-10-20 Manxi Wu , Saurabh Amin , Asuman Ozdaglar

Mutual coherence is a measure of similarity between two opinions. Although the notion comes from philosophy, it is essential for a wide range of technologies, e.g., the Wahl-O-Mat system. In Germany, this system helps voters to find…

Artificial Intelligence · Computer Science 2023-07-06 Gregor Betz , Vera Chekan , Tamara Mchedlidze

We present asymptotic results for the regression-adjusted version of approximate Bayesian computation introduced by Beaumont(2002). We show that for an appropriate choice of the bandwidth, regression adjustment will lead to a posterior…

Statistics Theory · Mathematics 2017-11-29 Wentao Li , Paul Fearnhead

We consider the problem of estimating a smooth functional of an unknown signal with discontinuity from Gaussian observations. The signal is a known function that depends on an unknown parameter. This problem is closely related to the famous…

Statistics Theory · Mathematics 2011-12-19 Farida Enikeeva

Aumann's famous Agreeing to Disagree Theorem states that if a group of agents share a common prior, update their beliefs by Bayesian conditioning based on private information, and have common knowledge of their posterior beliefs regarding…

Computer Science and Game Theory · Computer Science 2025-12-01 Eric Pacuit , Leo Yang

Ultra-fast, precise, and controlled amplitude surrogates are essential for future LHC event generation. First, we investigate the noise reduction and biases of network ensembles and outline a new method to learn well-calibrated systematic…

High Energy Physics - Phenomenology · Physics 2026-04-09 Henning Bahl , Nina Elmer , Tilman Plehn , Ramon Winterhalder

This paper presents a consensus algorithm for a multi-agent system where each agent has access to its imperfect own state and neighboring state measurements. The measurements are subject to deterministic disturbances and the proposed…

Systems and Control · Computer Science 2014-09-22 Mohammad Zamani , Iman Shames , Valery Ugrinovskii

We study the consensus formation for an agents based model, generalizing that originally proposed by Krause \cite{Kr}, by allowing the communication channels between any couple of agents to be switched on or off randomly, at each time step,…

Social and Information Networks · Computer Science 2026-03-26 Gianfelice Michele , Giuseppe Scola

Is the world quantum? An active research line in quantum foundations is devoted to exploring what constraints can rule out the postquantum theories that are consistent with experimentally observed results. We explore this question in the…

In the standard $q$-voter model, a given agent can change its opinion only if there is a full consensus of the opposite opinion within a group of influence of size $q$. A more realistic extension is the threshold $q$-voter, where a minimal…

Physics and Society · Physics 2020-05-28 A. R. Vieira , Antonio F. Peralta , Raul Toral , Maxi San Miguel , C. Anteneodo

Precision and accuracy, as two crucial criteria for quantum metrology, have previously lacked rigorous definitions and distinctions. In this paper, we provide a unified definition of precision and accuracy from the perspective of…

Quantum Physics · Physics 2025-07-15 Cong-Gang Song , Qing-yu Cai

We consider the estimation of a signal from the knowledge of its noisy linear random Gaussian projections, a problem relevant in compressed sensing, sparse superposition codes or code division multiple access just to cite few. There has…

Information Theory · Computer Science 2017-03-24 Jean Barbier , Mohamad Dia , Nicolas Macris , Florent Krzakala

We study a social learning scheme where at every time instant, each agent chooses to receive information from one of its neighbors at random. We show that under this sparser communication scheme, the agents learn the truth eventually and…

Multiagent Systems · Computer Science 2022-05-13 Yunus Inan , Mert Kayaalp , Emre Telatar , Ali H. Sayed

We derive a connection between performance of estimators the performance of the ideal observer on related detection tasks. Specifically we show how Shannon Information for the task of detecting a change in a parameter is related to the…

Information Theory · Computer Science 2019-07-24 Eric Clarkson

We consider distributed plurality consensus in a complete graph of size $n$ with $k$ initial opinions. We design an efficient and simple protocol in the asynchronous communication model that ensures that all nodes eventually agree on the…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-02-23 Robert Elsässer , Tom Friedetzky , Dominik Kaaser , Frederik Mallmann-Trenn , Horst Trinker

A distributed average consensus algorithm robust to a wide range of impulsive channel noise distributions is proposed. This work is the first of its kind in the literature to propose a consensus algorithm which relaxes the requirement of…

Systems and Control · Computer Science 2015-06-22 Sivaraman Dasarathan , Cihan Tepedelenlioglu , Mahesh Banavar , Andreas Spanias

The problem of fast point-to-point MIMO channel mutual information estimation is addressed, in the situation where the receiver undergoes unknown colored interference, whereas the channel with the transmitter is perfectly known. The…

Probability · Mathematics 2012-03-14 Abla Kammoun , Romain Couillet , Jamal Najim , Merouane Debbah

We present two classes of improved estimators for mutual information $M(X,Y)$, from samples of random points distributed according to some joint probability density $\mu(x,y)$. In contrast to conventional estimators based on binnings, they…

Statistical Mechanics · Physics 2009-11-10 Alexander Kraskov , Harald Stoegbauer , Peter Grassberger

This paper studies linear stochastic approximation (SA) algorithms and their application to multi-agent systems in engineering and sociology. As main contribution, we provide necessary and sufficient conditions for convergence of linear SA…

Optimization and Control · Mathematics 2018-09-07 Ge Chen , Xiaoming Duan , Wenjun Mei , Francesco Bullo