Description: Algorithms for Random Generation and Counting: A Markov Chain Approach by A. Sinclair Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description The underlying theme of the monograph is the study of two classical problems: counting the elements of a finite set of combinatorial structures, and generating them uniformly at random. Publisher Description This monograph is a slightly revised version of my PhD thesis [86], com pleted in the Department of Computer Science at the University of Edin burgh in June 1988, with an additional chapter summarising more recent developments. Some of the material has appeared in the form of papers [50,88]. The underlying theme of the monograph is the study of two classical problems: counting the elements of a finite set of combinatorial structures, and generating them uniformly at random. In their exact form, these prob lems appear to be intractable for many important structures, so interest has focused on finding efficient randomised algorithms that solve them ap proxim~ly, with a small probability of error. For most natural structures the two problems are intimately connected at this level of approximation, so it is natural to study them together. At the heart of the monograph is a single algorithmic paradigm: sim ulate a Markov chain whose states are combinatorial structures and which converges to a known probability distribution over them. This technique has applications not only in combinatorial counting and generation, but also in several other areas such as statistical physics and combinatorial optimi sation. The efficiency of the technique in any application depends crucially on the rate of convergence of the Markov chain. Details ISBN 0817636587 ISBN-13 9780817636586 Title Algorithms for Random Generation and Counting: A Markov Chain Approach Author A. Sinclair Format Hardcover Year 1993 Pages 147 Edition 1993rd Publisher Birkhauser Boston Inc GE_Item_ID:137926148; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 125.87 USD
Location: Fairfield, Ohio
End Time: 2024-12-23T03:06:28.000Z
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ISBN-13: 9780817636586
Book Title: Algorithms for Random Generation and Counting: A Markov Chain App
Number of Pages: VIII, 147 Pages
Language: English
Publication Name: Algorithms for Random Generation and Counting : a Markov Chain Approach
Publisher: Birkhäuser Boston
Subject: Programming / Algorithms, Probability & Statistics / Stochastic Processes, Probability & Statistics / General, Algebra / General, Applied
Publication Year: 1993
Item Weight: 31.7 Oz
Type: Textbook
Subject Area: Mathematics, Computers
Item Length: 9.3 in
Author: A. Sinclair
Series: Progress in Theoretical Computer Science Ser.
Item Width: 6.1 in
Format: Hardcover
