Finite Markov Chains and Algorithmic Applications (Paperback)

Olle Haggstrom

ISBN 10: 0521890012 / ISBN 13: 9780521890014

Published by Cambridge University Press, Cambridge, 2002

About this Item

Paperback. Based on a lecture course given at Chalmers University of Technology, this book is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before applying it to study a range of randomized algorithms with important applications in optimization and other problems in computing. Amongst the algorithms covered are the Markov chain Monte Carlo method, simulated annealing, and the recent Propp-Wilson algorithm. This book will appeal not only to mathematicians, but also to students of statistics and computer science. The subject matter is introduced in a clear and concise fashion and the numerous exercises included will help students to deepen their understanding. This text is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before using it to study a range of randomized algorithms with important applications in optimization and other problems in computing. The book will appeal not only to mathematicians, but to students of computer science who will discover much useful material. This clear and concise introduction to the subject has numerous exercises that will help students to deepen their understanding. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9780521890014

Bibliographic Details

• Title: Finite Markov Chains and Algorithmic Applications (Paperback)
• Publisher: Cambridge University Press, Cambridge
• Publication Date: 2002
• Language: English
• ISBN 10: 0521890012
• ISBN 13: 9780521890014
• Binding: Paperback
• Edition: 1st Edition
• Condition: new

About this title

Synopsis

This text is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory and Markov chains before using it to study a range of randomized algorithms with important applications in optimization and other problems in computing. The book will appeal not only to mathematicians, but to students of computer science who will discover much useful material. This clear and concise introduction to the subject has numerous exercises that will help students to deepen their understanding.

Book Description

Based on a lecture course given at Chalmers University, this book is ideal for advanced undergraduate or beginning graduate students. The author first develops the necessary background in probability theory before applying it to study a range of randomised algorithms that have important applications in computing. This book will appeal not only to mathematicians, but to students of computer science who will find much here that appeals. This is a clear and concise introduction to this subject and the numerous exercises included will help students to deepen their understanding.