Randomized algorithms approximation generation and counting

✍ Scribed by Russ Bubley

Publisher: Springer
Year: 2000
Tongue: English
Leaves: 166
Series: Distinguished Dissertations
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

📜 SIMILAR VOLUMES

Randomized Algorithms: Approximation, Ge

📁 Randomized Algorithms: Approximation, Generation and Counting

✍ Russ Bubley MA, PhD (auth.) 📂 Library 📅 2001 🏛 Springer-Verlag London 🌐 English

<p><B>Randomized Algorithms</B> 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 combinatoria

Algorithms for Random Generation and Cou

📁 Algorithms for Random Generation and Counting: A Markov Chain Approach

✍ Alistair Sinclair (auth.) 📂 Library 📅 1993 🏛 Birkhäuser Basel 🌐 English

<p>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]. Th

Algorithms for Random Generation and Cou

📁 Algorithms for Random Generation and Counting: A Markov Chain Approach

✍ A. Sinclair 📂 Library 📅 1993 🏛 Birkhäuser Boston 🌐 English

Randomization, Approximation, and Combin

📁 Randomization, Approximation, and Combinatorial Optimization. Algorithms and Techniques: Third International Workshop on Randomization and Approximation Techniques in Computer Science, and Second International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, RANDOM-APPROX’99, Berkeley, CA, USA, August 8-11, 1999.

✍ Andrei Z. Broder, Michael Mitzenmacher (auth.), Dorit S. Hochbaum, Klaus Jansen, 📂 Library 📅 1999 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

This book constitutes the refereed proceedings of the Third International Workshop on Randomization and Approximation Techniques in Computer Science, RANDOM'99, held jointly with the Second International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, APPROX'99, in Berk

Randomization, Approximation, and Combin

✍ Andrei Z. Broder, Michael Mitzenmacher (auth.), Dorit S. Hochbaum, Klaus Jansen, 📂 Library 📅 1999 🏛 Springer-Verlag Berlin Heidelberg 🌐 English

Lecture Notes for CS 6550: Advanced Grad

📁 Lecture Notes for CS 6550: Advanced Graduate Algorithms (Randomized and Approximation Algorithms)

✍ Eric Vigoda et al. 📂 Library 📅 2019 🏛 Georgia Institute of Technology 🌐 English