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Probabilistic Methods for Algorithmic Discrete Mathematics (Volume 16)

Probabilistic Methods for Algorithmic Discrete Mathematics (Volume 16)

Probabilistic Methods for Algorithmic Discrete Mathematics (Volume 16)
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Probabilistic Methods for Algorithmic Discrete Mathematics (Volume 16) Hardback - 1998

by Reed, B

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  • Hardback

Description

Springer, 1998. Volume 16. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9783540646228
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Details

  • Title Probabilistic Methods for Algorithmic Discrete Mathematics (Volume 16)
  • Author Reed, B
  • Binding Hardback
  • Edition 1st
  • Pages 325
  • Volumes 1
  • Language ENG
  • Publisher Springer
  • Publication date 1998
  • Bookseller's Inventory # 5569774
  • ISBN 9783540646228 / 3540646221
  • Weight 1.46 lbs (0.66 kg)
  • Dimensions 9.21 x 6.14 x 0.81 in (23.39 x 15.60 x 2.06 cm)
  • Category Mathematics
  • Library of Congress Catalogue Number 98036217
  • Dewey Decimal Code 004.015

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Reader reviews for Probabilistic Methods for Algorithmic Discrete Mathematics (Volume 16)

From the publisher

Leave nothing to chance. This cliche embodies the common belief that ran- domness has no place in carefully planned methodologies, every step should be spelled out, each i dotted and each t crossed. In discrete mathematics at least, nothing could be further from the truth. Introducing random choices into algorithms can improve their performance. The application of proba- bilistic tools has led to the resolution of combinatorial problems which had resisted attack for decades. The chapters in this volume explore and celebrate this fact. Our intention was to bring together, for the first time, accessible discus- sions of the disparate ways in which probabilistic ideas are enriching discrete mathematics. These discussions are aimed at mathematicians with a good combinatorial background but require only a passing acquaintance with the basic definitions in probability (e.g. expected value, conditional probability). A reader who already has a firm grasp on the area will be interested in the original research, novel syntheses, and discussions of ongoing developments scattered throughout the book. Some of the most convincing demonstrations of the power of these tech- niques are randomized algorithms for estimating quantities which are hard to compute exactly. One example is the randomized algorithm of Dyer, Frieze and Kannan for estimating the volume of a polyhedron. To illustrate these techniques, we consider a simple related problem. Suppose S is some region of the unit square defined by a system of polynomial inequalities: Pi (x. y) o.

From the rear cover

The book gives an accessible account of modern pro- babilistic methods for analyzing combinatorial structures and algorithms. Each topic is approached in a didactic manner but the most recent developments are linked to the basic ma- terial. Extensive lists of references and a detailed index will make this a useful guide for graduate students and researchers. Special features included:
- a simple treatment of Talagrand inequalities and their applications
- an overview and many carefully worked out examples of the probabilistic analysis of combinatorial algorithms
- a discussion of the "exact simulation" algorithm (in the context of Markov Chain Monte Carlo Methods)
- a general method for finding asymptotically optimal or near optimal graph colouring, showing how the probabilistic method may be fine-tuned to explit the structure of the underlying graph
- a succinct treatment of randomized algorithms and derandomization techniques
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