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Probability on Discrete Structures

Posted By: AvaxGenius
Date: 19 Sep 2022 16:26:17
Probability on Discrete Structures

Probability on Discrete Structures by Harry Kesten
English | PDF | 2004 | 358 Pages | ISBN : 3540008454 | 36.6 MB

Most probability problems involve random variables indexed by space and/or time. These problems almost always have a version in which space and/or time are taken to be discrete. This volume deals with areas in which the discrete version is more natural than the continuous one, perhaps even the only one than can be formulated without complicated constructions and machinery.
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Sojourns in Probability Theory and Statistical Physics - III (Repost)

Posted By: AvaxGenius
Date: 5 Jun 2022 11:08:06
Sojourns in Probability Theory and Statistical Physics - III (Repost)

Sojourns in Probability Theory and Statistical Physics - III: Interacting Particle Systems and Random Walks, A Festschrift for Charles M. Newman by Vladas Sidoravicius
English | EPUB | 2019 | 327 Pages | ISBN : 981150301X | 29.2 MB

Charles M. (Chuck) Newman has been a leader in Probability Theory and Statistical Physics for nearly half a century. This three-volume set is a celebration of the far-reaching scientific impact of his work. It consists of articles by Chuck’s collaborators and colleagues across a number of the fields to which he has made contributions of fundamental significance. This publication was conceived during a conference in 2016 at NYU Shanghai that coincided with Chuck`s 70th birthday.
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Stochastic Approximation and Recursive Algorithms and Applications, Second Edition (Repost)

Posted By: AvaxGenius
Date: 21 Mar 2020 23:06:59
Stochastic Approximation and Recursive Algorithms and Applications, Second Edition (Repost)

Stochastic Approximation and Recursive Algorithms and Applications, Second Edition by Harold J. Kushner
English | PDF | 2003 | 485 Pages | ISBN : 1441918477 | 4.65 MB

This revised and expanded second edition presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. There is a complete development of both probability one and weak convergence methods for very general noise processes. The proofs of convergence use the ODE method, the most powerful to date. The assumptions and proof methods are designed to cover the needs of recent applications.
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