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Have you ever wondered what Marilyn Monroe, Pamela Anderson, Dolly Parton, Farrah Fawcett, and Cindy Crawford all have in common? It's not just their legendary status in the entertainment industry - they've all graced the pages of Playboy Magazine at some point in their illustrious careers. Experience the timeless allure of these global icons and many more in the complete Playboy Archive!

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Algorithmic Algebraic Combinatorics and Gröbner Bases (Repost)

Posted By: AvaxGenius
Date: 20 Jun 2022 01:22:32
Algorithmic Algebraic Combinatorics and Gröbner Bases (Repost)

Algorithmic Algebraic Combinatorics and Gröbner Bases by Mikhail Klin
English | PDF | 2009 | 315 Pages | ISBN : 3642019595 | 3.8 MB

This collection of tutorial and research papers introduces readers to diverse areas of modern pure and applied algebraic combinatorics and finite geometries with a special emphasis on algorithmic aspects and the use of the theory of Gröbner bases.
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Garden Lighting

Posted By: l3ivo
Date: 29 Jan 2022 14:35:57
Garden Lighting

John Raine, "Garden Lighting"
English | 2001 | ISBN: 1571456929 | 128 pages | DJVU | 12.9 MB
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Large Deviations Techniques and Applications, Second Edition (Repost)

Posted By: AvaxGenius
Date: 3 Jan 2021 19:57:06
Large Deviations Techniques and Applications, Second Edition (Repost)

Large Deviations Techniques and Applications, Second Edition by Amir Dembo
Engilsh | PDF | 2009 | 409 Pages | ISBN : 3642033105 | 4.1 MB

The theory of large deviations deals with the evaluation, for a family of probability measures parameterized by a real valued variable, of the probabilities of events which decay exponentially in the parameter.
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Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions

Posted By: AvaxGenius
Date: 9 Aug 2020 15:23:58
Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions

Tools for Statistical Inference: Methods for the Exploration of Posterior Distributions and Likelihood Functions by Martin A. Tanner
English | PDF | 1993 | 166 Pages | ISBN : 0387946888 | 12.22 MB

This book provides a unified introduction to a variety of computational algorithms for likelihood and Bayesian inference. In this second edition, I have attempted to expand the treatment of many of the techniques dis­ cussed, as well as include important topics such as the Metropolis algorithm and methods for assessing the convergence of a Markov chain algorithm.
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