Can I read Concentration of Measure for the Analysis of Randomized Algorithms on EtoBox?

Concentration of Measure for the Analysis of Randomized Algorithms by Devdatt P. Dubhashi; Alessandro Panconesi is a nonfiction available to read on EtoBox.

What is Concentration of Measure for the Analysis of Randomized Algorithms about?

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.

Who reads Concentration of Measure for the Analysis of Randomized Algorithms?

Author

Devdatt P. Dubhashi; Alessandro Panconesi

Publisher

Cambridge University Press (Virtual Publishing)

Published

2009

Language

EN

ISBN

9780511581274

Category

nonfiction

Subjects

Mathematics, Stem