Randomized Algorithms: Approximation, Generation, and Counting
Author | : Russ Bubley |
Publisher | : Springer Science & Business Media |
Total Pages | : 167 |
Release | : 2012-12-06 |
ISBN-10 | : 9781447106951 |
ISBN-13 | : 1447106954 |
Rating | : 4/5 (954 Downloads) |
Download or read book Randomized Algorithms: Approximation, Generation, and Counting written by Russ Bubley and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomized Algorithms discusses two problems of fine pedigree: counting and generation, both of which are of fundamental importance to discrete mathematics and probability. When asking questions like "How many are there?" and "What does it look like on average?" of families of combinatorial structures, answers are often difficult to find -- we can be blocked by seemingly intractable algorithms. Randomized Algorithms shows how to get around the problem of intractability with the Markov chain Monte Carlo method, as well as highlighting the method's natural limits. It uses the technique of coupling before introducing "path coupling" a new technique which radically simplifies and improves upon previous methods in the area.