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Journal ArticleDOI

Reaching a Consensus

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TLDR
In this article, the authors consider a group of individuals who must act together as a team or committee, and assume that each individual in the group has his own subjective probability distribution for the unknown value of some parameter.
Abstract
Consider a group of individuals who must act together as a team or committee, and suppose that each individual in the group has his own subjective probability distribution for the unknown value of some parameter. A model is presented which describes how the group might reach agreement on a common subjective probability distribution for the parameter by pooling their individual opinions. The process leading to the consensus is explicitly described and the common distribution that is reached is explicitly determined. The model can also be applied to problems of reaching a consensus when the opinion of each member of the group is represented simply as a point estimate of the parameter rather than as a probability distribution.

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Citations
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Proceedings ArticleDOI

Demarcating Endogenous and Exogenous Opinion Diffusion Process on Social Networks

TL;DR: CherryPick is designed, a novel learning machinery that classifies the opinions and users by solving a joint inference task in message and user set, from a temporal stream of sentiment messages and can precisely determine the quality of a set of control users, which together with the proposed online shaping strategy, consistently steers the opinion dynamics more effectively than several state-of-the-art baselines.
Journal ArticleDOI

Computer science and decision theory

TL;DR: This paper reviews applications in computer science that decision theorists have addressed for years, discusses the requirements posed by these applications that place great strain on decision theory/social science methods, and explores applications in the social and decision sciences of newer decision-theoretic methods developed with computer science applications in mind.
Journal ArticleDOI

From classical to quantum walks with stochastic resetting on networks.

TL;DR: This work provides a framework of classical and quantum walks whose evolution is determined by graph Laplacians, and studies the influence of quantum effects on the stationary and long-time average probability distribution by interpolating between the classical and Quantum regime.

Asset Allocation in Finance: A Bayesian Perspective

TL;DR: In this paper, the authors study an investor who wishes to maximize the expected long-run growth of the market and derive the Kelly criteria for optimal bet size and Merton's allocation rule for risky stocks.
Journal ArticleDOI

Robustness of large-scale stochastic matrices to localized perturbations

TL;DR: In this article, the authors derived upper bounds on the total variation distance between the invariant probability vectors of two stochastic matrices differing on a subset of rows of rows.
References
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Book

Stochastic processes

J. L. Doob, +1 more
Book

A first course in stochastic processes

TL;DR: In this paper, the Basic Limit Theorem of Markov Chains and its applications are discussed and examples of continuous time Markov chains are presented. But they do not cover the application of continuous-time Markov chain in matrix analysis.
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