Concentration of Measure for the Analysis of Randomized Algorithms
Randomized algorithms have become a central part of the algorithms curriculum based on their increasingly widespread use in modern applications. Get and download textbook Concentration of Measure for the Analysis of Randomized Algorithms for free
Concentration of Measure for the Analysis of Randomized Algorithms
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 tool kit from the Chernoff-Hoeffding (CH) 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 CH bounds in dependent settings. The authors emphasize comparative study of the different methods, Concentration of Measure for the Analysis of Randomized Algorithms new edition
Download free books for Concentration Of Measure For The Analysis Of Randomized Algorithms, Devdatt P. D
author alessandro panconesi author devdatt p dubhashi format paperback language english publication year 12 03 2012 subject mathematics sciences subject 2 science mathematics textbooks study guides themonsterbookshop co uk in titles description add my store to your favorites and receive my email newsletters about new items and special promotions general interest concentration of measure for the analysis of randomized algorithms item details title concentration of measure for the analysis of rand
Concentration of Measure for the Analysis of Randomized Algorithms Ucmbs 9781107606609 09781107606609
Randomized algorithms have become a central part of the algorithms curriculum, based on their increasingly widespread use in modern applications. This Book p
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 tool kit from the Chernoff-Hoeffding (CH) 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 th
Concentration of Measure for the Analysis of Randomized Algorithms Textbook
The authors emphasize comparative study of the different methods,
