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

Author: A. Sinclair

Publisher: Springer Science & Business Media

Published: 1993-02

Total Pages: 161

ISBN-13: 0817636587

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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.

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

Author: A. Sinclair

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 156

ISBN-13: 1461203236

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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.

Randomized Algorithms: Approximation, Generation, and Counting
Randomized Algorithms: Approximation, Generation, and Counting

Author: Russ Bubley

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 167

ISBN-13: 1447106954

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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.

Random Number Generators--Principles and Practices
Random Number Generators--Principles and Practices

Author: David Johnston

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2018

Total Pages: 516

ISBN-13: 1501506269

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Random Number Generators, Principles and Practices has been written for programmers, hardware engineers, and sophisticated hobbyists interested in understanding random numbers generators and gaining the tools necessary to work with random number generators with confidence and knowledge. Using an approach that employs clear diagrams and running code examples rather than excessive mathematics, random number related topics such as entropy estimation, entropy extraction, entropy sources, PRNGs, randomness testing, distribution generation, and many others are exposed and demystified. If you have ever Wondered how to test if data is really random Needed to measure the randomness of data in real time as it is generated Wondered how to get randomness into your programs Wondered whether or not a random number generator is trustworthy Wanted to be able to choose between random number generator solutions Needed to turn uniform random data into a different distribution Needed to ensure the random numbers from your computer will work for your cryptographic application Wanted to combine more than one random number generator to increase reliability or security Wanted to get random numbers in a floating point format Needed to verify that a random number generator meets the requirements of a published standard like SP800-90 or AIS 31 Needed to choose between an LCG, PCG or XorShift algorithm Then this might be the book for you.

Random Numbers and Computers
Random Numbers and Computers

Author: Ronald T. Kneusel

Publisher: Springer

Published: 2018-04-05

Total Pages: 266

ISBN-13: 3319776975

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This book covers pseudorandom number generation algorithms, evaluation techniques, and offers practical advice and code examples. Random Numbers and Computers is an essential introduction or refresher on pseudorandom numbers in computer science. The first comprehensive book on the topic, readers are provided with a practical introduction to the techniques of pseudorandom number generation, including how the algorithms work and how to test the output to decide if it is suitable for a particular purpose. Practical applications are demonstrated with hands-on presentation and descriptions that readers can apply directly to their own work. Examples are in C and Python and given with an emphasis on understanding the algorithms to the point of practical application. The examples are meant to be implemented, experimented with and improved/adapted by the reader.

Probabilistic Methods for Algorithmic Discrete Mathematics
Probabilistic Methods for Algorithmic Discrete Mathematics

Author: Michel Habib

Publisher: Springer Science & Business Media

Published: 2013-03-14

Total Pages: 342

ISBN-13: 3662127881

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Leave nothing to chance. This cliche embodies the common belief that ran domness has no place in carefully planned methodologies, every step should be spelled out, each i dotted and each t crossed. In discrete mathematics at least, nothing could be further from the truth. Introducing random choices into algorithms can improve their performance. The application of proba bilistic tools has led to the resolution of combinatorial problems which had resisted attack for decades. The chapters in this volume explore and celebrate this fact. Our intention was to bring together, for the first time, accessible discus sions of the disparate ways in which probabilistic ideas are enriching discrete mathematics. These discussions are aimed at mathematicians with a good combinatorial background but require only a passing acquaintance with the basic definitions in probability (e.g. expected value, conditional probability). A reader who already has a firm grasp on the area will be interested in the original research, novel syntheses, and discussions of ongoing developments scattered throughout the book. Some of the most convincing demonstrations of the power of these tech niques are randomized algorithms for estimating quantities which are hard to compute exactly. One example is the randomized algorithm of Dyer, Frieze and Kannan for estimating the volume of a polyhedron. To illustrate these techniques, we consider a simple related problem. Suppose S is some region of the unit square defined by a system of polynomial inequalities: Pi (x. y) ~ o.

Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms
Proceedings of the Sixth Annual ACM-SIAM Symposium on Discrete Algorithms

Author:

Publisher: SIAM

Published: 1995-01-01

Total Pages: 668

ISBN-13: 9780898713497

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The proceedings of the January 1995 symposium, sponsored by the ACM Special Interest Group on Algorithms and Computation Theory and the SIAM Activity Group on Discrete Mathematics, comprise 70 papers. Among the topics: on-line approximate list indexing with applications; finding subsets maximizing minimum structures; register allocation in structured programs; and splay trees for data compression. No index. Annotation copyright by Book News, Inc., Portland, OR

Database Systems for Advanced Applications
Database Systems for Advanced Applications

Author: Jeffrey Xu Yu

Publisher: Springer

Published: 2011-04-09

Total Pages: 604

ISBN-13: 3642201490

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This two volume set LNCS 6587 and LNCS 6588 constitutes the refereed proceedings of the 16th International Conference on Database Systems for Advanced Applications, DASFAA 2011, held in Saarbrücken, Germany, in April 2010. The 53 revised full papers and 12 revised short papers presented together with 2 invited keynote papers, 22 demonstration papers, 4 industrial papers, 8 demo papers, and the abstract of 1 panel discussion, were carefully reviewed and selected from a total of 225 submissions. The topics covered are social network, social network and privacy, data mining, probability and uncertainty, stream processing, graph, XML, XML and graph, similarity, searching and digital preservation, spatial queries, query processing, as well as indexing and high performance.

Computing and Combinatorics
Computing and Combinatorics

Author: Zhipeng Cai

Publisher: Springer

Published: 2014-07-05

Total Pages: 704

ISBN-13: 3319087835

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This book constitutes the refereed proceedings of the 20th International Conference on Computing and Combinatorics, COCOON 2014, held in Atlanta, GA, USA, in August 2014. The 51 revised full papers presented were carefully reviewed and selected from 110 submissions. There was a co-organized workshop on computational social networks (CSoNet 2014) where 8 papers were accepted. The papers cover the following topics: sampling and randomized methods; logic, algebra and automata; database and data structures; parameterized complexity and algorithms; computational complexity; computational biology and computational geometry; approximation algorithm; graph theory and algorithms; game theory and cryptography; scheduling algorithms and circuit complexity and CSoNet.

Handbook of Satisfiability
Handbook of Satisfiability

Author: A. Biere

Publisher: IOS Press

Published: 2021-05-05

Total Pages: 1486

ISBN-13: 1643681613

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Propositional logic has been recognized throughout the centuries as one of the cornerstones of reasoning in philosophy and mathematics. Over time, its formalization into Boolean algebra was accompanied by the recognition that a wide range of combinatorial problems can be expressed as propositional satisfiability (SAT) problems. Because of this dual role, SAT developed into a mature, multi-faceted scientific discipline, and from the earliest days of computing a search was underway to discover how to solve SAT problems in an automated fashion. This book, the Handbook of Satisfiability, is the second, updated and revised edition of the book first published in 2009 under the same name. The handbook aims to capture the full breadth and depth of SAT and to bring together significant progress and advances in automated solving. Topics covered span practical and theoretical research on SAT and its applications and include search algorithms, heuristics, analysis of algorithms, hard instances, randomized formulae, problem encodings, industrial applications, solvers, simplifiers, tools, case studies and empirical results. SAT is interpreted in a broad sense, so as well as propositional satisfiability, there are chapters covering the domain of quantified Boolean formulae (QBF), constraints programming techniques (CSP) for word-level problems and their propositional encoding, and satisfiability modulo theories (SMT). An extensive bibliography completes each chapter. This second edition of the handbook will be of interest to researchers, graduate students, final-year undergraduates, and practitioners using or contributing to SAT, and will provide both an inspiration and a rich resource for their work. Edmund Clarke, 2007 ACM Turing Award Recipient: "SAT solving is a key technology for 21st century computer science." Donald Knuth, 1974 ACM Turing Award Recipient: "SAT is evidently a killer app, because it is key to the solution of so many other problems." Stephen Cook, 1982 ACM Turing Award Recipient: "The SAT problem is at the core of arguably the most fundamental question in computer science: What makes a problem hard?"