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An introduction to probability theory and its applications

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The article was published on 1950-01-01 and is currently open access. It has received 31532 citations till now. The article focuses on the topics: Probability and statistics & Imprecise probability.

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Controlled Markov processes and viscosity solutions

TL;DR: In this paper, an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions is given, as well as a concise introduction to two-controller, zero-sum differential games.
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On the number of segregating sites in genetical models without recombination.

TL;DR: The distribution is obtained for the number of segregating sites observed in a sample from a population which is subject to recurring, new, mutations but not subject to recombination, and applies approximately to three population models.
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Detection of abrupt changes: theory and application

TL;DR: A unified framework for the design and the performance analysis of the algorithms for solving change detection problems and links with the analytical redundancy approach to fault detection in linear systems are established.
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A kernel two-sample test

TL;DR: This work proposes a framework for analyzing and comparing distributions, which is used to construct statistical tests to determine if two samples are drawn from different distributions, and presents two distribution free tests based on large deviation bounds for the maximum mean discrepancy (MMD).
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The Proper Orthogonal Decomposition in the Analysis of Turbulent Flows

TL;DR: The Navier-Stokes equations are well-known to be a good model for turbulence as discussed by the authors, and the results of well over a century of increasingly sophisticated experiments are available at our disposal.