[PDF.33kn] Concentration of Measure for the Analysis of Randomized Algorithms

Concentration of Measure for the Analysis of Randomized Algorithms

[PDF.fo00] Concentration of Measure for the Analysis of Randomized Algorithms

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 | #2244409 in eBooks |  2009-06-15 |  2009-06-15 | File type: PDF

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||2 of 2 people found the following review helpful.| good, but needs another proof reading|By Shlomo Moran|pro: The presentation of Chernoff bounds brings better intuition and is more didactic than in other textbooks I know.
con: In this edition there are few typos/inaccuracies, and some essential parts of the proofs are left to the reader. If these are fixed, it would be an excellent textbook for this subject.|2 of 2 peopl| |Pre-Publication : "Concentration bounds are at the core of probabilistic analysis of algorithms. This excellent text provides a comprehensive treatment of this important subject, ranging from the very basic to the more advance tools, including some recent dev

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 s...

You easily download any file type for your gadget.Concentration of Measure for the Analysis of Randomized Algorithms   |  Devdatt P. Dubhashi, Alessandro Panconesi. Which are the reasons I like to read books. Great story by a great author.

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