The book gives an accessible account of modern probabilistic methods for analyzing combinatorial structures and algorithms. It will be an useful guide for graduate students and researchers. Special features included: a simple treatment of Talagrand's 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 exploit the structure of the underlying graph; a succinct treatment of randomized algorithms and derandomization techniques.
Probabilistic Methods for Algorithmic Discrete Mathematics
and over one million other books are available for Amazon Kindle.
Learn more
FREE Two-Day Shipping for students on millions of items. Learn more |
| ||||||||||||||||||||||||
Book Description
Special Offers and Product Promotions
- Buy $50 in qualifying physical textbooks, get $5 in Amazon MP3 Credit. Here's how (restrictions apply)
Editorial Reviews
From the Back 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
Product Details
Would you like to update product info or give feedback on images?
|
Customer Reviews
|
There are no customer reviews yet.
|
|||
|
Video reviews
|
Inside This Book
(learn more)
Key Phrases - Capitalized Phrases (CAPs):
(learn more)
Local Lemma, Monte Carlo, First Moment Method, Foundations of Computer Science, New York, Mathematical Programming, Operations Research, Las Vegas, Discrete Algorithms, Simple Concentration Bound, Academic Press, John Wiley, Lecture Notes, Cambridge University Press, Proceedings of the Cambridge Philosophical Society, Annual Symposium, Discrete Applied Mathematics, Journal of Algorithms, Technical Report, Annals of Applied Probability, Annals of Probability, Computer Society Press, Journal of Combinatorial Theory, University of California New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Local Lemma, Monte Carlo, First Moment Method, Foundations of Computer Science, New York, Mathematical Programming, Operations Research, Las Vegas, Discrete Algorithms, Simple Concentration Bound, Academic Press, John Wiley, Lecture Notes, Cambridge University Press, Proceedings of the Cambridge Philosophical Society, Annual Symposium, Discrete Applied Mathematics, Journal of Algorithms, Technical Report, Annals of Applied Probability, Annals of Probability, Computer Society Press, Journal of Combinatorial Theory, University of California New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 46
books:
See all 46 books this book cites
21
books
cite this book:
See all 21 books citing this book
- The Probabilistic Method (Wiley Series in Discrete Mathematics and Optimization) by Noga Alon on 4 pages
- Computer Science: A Concise Introduction by Ian Robertson Sinclair on 4 pages
- Randomized Algorithms by Rajeev Motwani on page 93, page 114, and page 247
- Combinatorial Optimization: Annotated Bibliographies by M. O'Heigeartaigh on page 90, and page 114
- Computer Science by Richard Jones on page 193, and page 194
See all 46 books this book cites
- Probability on Discrete Structures by Harry Kesten on page 70, and page 120
- Combinatorial Matrix Classes (Encyclopedia of Mathematics and its Applications) by Richard A. Brualdi on page 308, and Back Matter
- Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised ... / Lecture Notes in Artificial Intelligence) by Olivier Bousquet on page 206, and Back Matter
- Average Case Analysis of Algorithms on Sequences (Wiley Series in Discrete Mathematics and Optimization) by Wojciech Szpankowski in Back Matter
- Proceedings of the Sixth International Conference on Difference Equations Augsburg, Germany 2001: New Progress in Difference Equations by Bernd Aulbach on page 60
See all 21 books citing this book
Books on Related Topics
(learn more)
|
What Other Items Do Customers Buy After Viewing This Item?
Suggested Tags from Similar Products(What's this?)Be the first one to add a relevant tag (keyword that's strongly related to this product).
|
Customer Discussions
|
This product's forum
Active discussions in related forums
Search Customer Discussions
|
Related forums
|
Listmania!
So You'd Like to...
Look for Similar Items by Category
- Books > Computers & Technology > Computer Science
- Books > Computers & Technology > Programming > Algorithms
- Books > New & Used Textbooks > Computer Science > Programming Languages
- Books > New & Used Textbooks > Science & Mathematics > Mathematics > Algebra & Trigonometry
- Books > New & Used Textbooks > Science & Mathematics > Mathematics > Statistics
- Books > Science & Math > Mathematics
