Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024


Concentration of Measure for the Analysis of Randomized Algorithms

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Devdatt P. Dubhashi 作者
Cambridge University Press
譯者
2009-6-15 出版日期
214 頁數
GBP 93.00 價格
Hardcover
叢書系列
9780521884273 圖書編碼

Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 圖書標籤: 算法  數學  隨機算法的應用  概率  concentration_inequality  Math  CS   


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Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 epub 下載 mobi 下載 pdf 下載 txt 下載 2024

Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 epub 下載 pdf 下載 mobi 下載 txt 下載 2024

Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 pdf 下載 txt下載 epub 下載 mobi 下載 2024



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Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 著者簡介


Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 著者簡介


Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 pdf 下載 txt下載 epub 下載 mobi 在線電子書下載

Concentration of Measure for the Analysis of Randomized Algorithms 在線電子書 圖書描述

Randomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This book presents a coherent and unified treatment of probabilistic techniques for obtaining high probability estimates on the performance of randomized algorithms. It covers the basic toolkit from the Chernoff-Hoeffding bounds to more sophisticated techniques like martingales and isoperimetric inequalities, as well as some recent developments like Talagrand's inequality, transportation cost inequalities and log-Sobolev inequalities. Along the way, variations on the basic theme are examined, such as Chernoff-Hoeffding bounds in dependent settings. The authors emphasise comparative study of the different methods, highlighting respective strengths and weaknesses in concrete example applications. The exposition is tailored to discrete settings sufficient for the analysis of algorithms, avoiding unnecessary measure-theoretic details, thus making the book accessible to computer scientists as well as probabilists and discrete mathematicians.

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