Probabilistic Methods For Algorithmic Discrete Mathematics

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Probabilistic Methods for Algorithmic Discrete Mathematics

Author : Michel Habib
Publisher : Springer Science & Business Media
ISBN 13 : 3662127881
Total Pages : 342 pages
Book Rating : 4.6/5 (621 download)

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Book Synopsis Probabilistic Methods for Algorithmic Discrete Mathematics by : Michel Habib

Download or read book Probabilistic Methods for Algorithmic Discrete Mathematics written by Michel Habib and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The Probabilistic Method

Author : Noga Alon
Publisher : John Wiley & Sons
ISBN 13 : 1119061962
Total Pages : 400 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis The Probabilistic Method by : Noga Alon

Download or read book The Probabilistic Method written by Noga Alon and published by John Wiley & Sons. This book was released on 2015-10-28 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Third Edition “Researchers of any kind of extremal combinatorics or theoretical computer science will welcome the new edition of this book.” - MAA Reviews Maintaining a standard of excellence that establishes The Probabilistic Method as the leading reference on probabilistic methods in combinatorics, the Fourth Edition continues to feature a clear writing style, illustrative examples, and illuminating exercises. The new edition includes numerous updates to reflect the most recent developments and advances in discrete mathematics and the connections to other areas in mathematics, theoretical computer science, and statistical physics. Emphasizing the methodology and techniques that enable problem-solving, The Probabilistic Method, Fourth Edition begins with a description of tools applied to probabilistic arguments, including basic techniques that use expectation and variance as well as the more advanced applications of martingales and correlation inequalities. The authors explore where probabilistic techniques have been applied successfully and also examine topical coverage such as discrepancy and random graphs, circuit complexity, computational geometry, and derandomization of randomized algorithms. Written by two well-known authorities in the field, the Fourth Edition features: Additional exercises throughout with hints and solutions to select problems in an appendix to help readers obtain a deeper understanding of the best methods and techniques New coverage on topics such as the Local Lemma, Six Standard Deviations result in Discrepancy Theory, Property B, and graph limits Updated sections to reflect major developments on the newest topics, discussions of the hypergraph container method, and many new references and improved results The Probabilistic Method, Fourth Edition is an ideal textbook for upper-undergraduate and graduate-level students majoring in mathematics, computer science, operations research, and statistics. The Fourth Edition is also an excellent reference for researchers and combinatorists who use probabilistic methods, discrete mathematics, and number theory. Noga Alon, PhD, is Baumritter Professor of Mathematics and Computer Science at Tel Aviv University. He is a member of the Israel National Academy of Sciences and Academia Europaea. A coeditor of the journal Random Structures and Algorithms, Dr. Alon is the recipient of the Polya Prize, The Gödel Prize, The Israel Prize, and the EMET Prize. Joel H. Spencer, PhD, is Professor of Mathematics and Computer Science at the Courant Institute of New York University. He is the cofounder and coeditor of the journal Random Structures and Algorithms and is a Sloane Foundation Fellow. Dr. Spencer has written more than 200 published articles and is the coauthor of Ramsey Theory, Second Edition, also published by Wiley.

Algorithms and Data Structures

Author : Helmut Knebl
Publisher : Springer Nature
ISBN 13 : 303059758X
Total Pages : 349 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Algorithms and Data Structures by : Helmut Knebl

Download or read book Algorithms and Data Structures written by Helmut Knebl and published by Springer Nature. This book was released on 2020-10-31 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a central topic in any computer science curriculum. To distinguish this textbook from others, the author considers probabilistic methods as being fundamental for the construction of simple and efficient algorithms, and in each chapter at least one problem is solved using a randomized algorithm. Data structures are discussed to the extent needed for the implementation of the algorithms. The specific algorithms examined were chosen because of their wide field of application. This book originates from lectures for undergraduate and graduate students. The text assumes experience in programming algorithms, especially with elementary data structures such as chained lists, queues, and stacks. It also assumes familiarity with mathematical methods, although the author summarizes some basic notations and results from probability theory and related mathematical terminology in the appendices. He includes many examples to explain the individual steps of the algorithms, and he concludes each chapter with numerous exercises.

Probability and Computing

Author : Michael Mitzenmacher
Publisher : Cambridge University Press
ISBN 13 : 1139643789
Total Pages : 372 pages
Book Rating : 4.1/5 (396 download)

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Book Synopsis Probability and Computing by : Michael Mitzenmacher

Download or read book Probability and Computing written by Michael Mitzenmacher and published by Cambridge University Press. This book was released on 2005-01-31 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols. This 2005 textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It assumes only an elementary background in discrete mathematics and gives a rigorous yet accessible treatment of the material, with numerous examples and applications. The first half of the book covers core material, including random sampling, expectations, Markov's inequality, Chevyshev's inequality, Chernoff bounds, the probabilistic method and Markov chains. The second half covers more advanced topics such as continuous probability, applications of limited independence, entropy, Markov chain Monte Carlo methods and balanced allocations. With its comprehensive selection of topics, along with many examples and exercises, this book is an indispensable teaching tool.

Graph Colouring and the Probabilistic Method

Author : Michael Molloy
Publisher : Springer Science & Business Media
ISBN 13 : 3642040160
Total Pages : 320 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Graph Colouring and the Probabilistic Method by : Michael Molloy

Download or read book Graph Colouring and the Probabilistic Method written by Michael Molloy and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, many major advances have been made in the field of graph coloring via the probabilistic method. This monograph, by two of the best on the topic, provides an accessible and unified treatment of these results, using tools such as the Lovasz Local Lemma and Talagrand's concentration inequality.

Probabilistic Methods in Discrete Mathematics

Author : V. F. Kolchin
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3112314107
Total Pages : 400 pages
Book Rating : 4.1/5 (123 download)

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Book Synopsis Probabilistic Methods in Discrete Mathematics by : V. F. Kolchin

Download or read book Probabilistic Methods in Discrete Mathematics written by V. F. Kolchin and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-05-18 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Probabilistic Methods in Discrete Mathematics".

Probability and Computing

Author : Michael Mitzenmacher
Publisher :
ISBN 13 :
Total Pages : 368 pages
Book Rating : 4.:/5 (113 download)

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Book Synopsis Probability and Computing by : Michael Mitzenmacher

Download or read book Probability and Computing written by Michael Mitzenmacher and published by . This book was released on 2005 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomization and probabilistic techniques play an important role in modern computer science, with applications ranging from combinatorial optimization and machine learning to communication networks and secure protocols. This textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It assumes only an elementary background in discrete mathematics and gives a rigorous yet accessible treatment of the material, with numerous examples and applications. The first half of the book covers core material, including random sampling, expectations, Markov's inequality, Chevyshev's inequality, Chernoff bounds, balls and bins models, the probabilistic method, and Markov chains. In the second half, the authors delve into more advanced topics such as continuous probability, applications of limited independence, entropy, Markov chain Monte Carlo methods, coupling, martingales, and balanced allocations. With its comprehensive selection of topics, along with many examples and exercises, this book is an indispensable teaching tool.

Ten Lectures on the Probabilistic Method

Author : Joel Spencer
Publisher : SIAM
ISBN 13 : 9781611970074
Total Pages : 98 pages
Book Rating : 4.9/5 (7 download)

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Book Synopsis Ten Lectures on the Probabilistic Method by : Joel Spencer

Download or read book Ten Lectures on the Probabilistic Method written by Joel Spencer and published by SIAM. This book was released on 1994-01-01 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: This update of the 1987 title of the same name is an examination of what is currently known about the probabilistic method, written by one of its principal developers. Based on the notes from Spencer's 1986 series of ten lectures, this new edition contains an additional lecture: The Janson inequalities. These inequalities allow accurate approximation of extremely small probabilities. A new algorithmic approach to the Lovasz Local Lemma, attributed to Jozsef Beck, has been added to Lecture 8, as well. Throughout the monograph, Spencer retains the informal style of his original lecture notes and emphasizes the methodology, shunning the more technical "best possible" results in favor of clearer exposition. The book is not encyclopedic--it contains only those examples that clearly display the methodology. The probabilistic method is a powerful tool in graph theory, combinatorics, and theoretical computer science. It allows one to prove the existence of objects with certain properties (e.g., colorings) by showing that an appropriately defined random object has positive probability of having those properties.

Discrete Algorithmic Mathematics

Author : Stephen B. Maurer
Publisher : CRC Press
ISBN 13 : 143986375X
Total Pages : 793 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Discrete Algorithmic Mathematics by : Stephen B. Maurer

Download or read book Discrete Algorithmic Mathematics written by Stephen B. Maurer and published by CRC Press. This book was released on 2005-01-21 with total page 793 pages. Available in PDF, EPUB and Kindle. Book excerpt: Thoroughly revised for a one-semester course, this well-known and highly regarded book is an outstanding text for undergraduate discrete mathematics. It has been updated with new or extended discussions of order notation, generating functions, chaos, aspects of statistics, and computational biology. Written in a lively, clear style that talks to th

Mathematics and Computer Science

Author : Daniele Gardy
Publisher : Birkhäuser
ISBN 13 : 3034884052
Total Pages : 337 pages
Book Rating : 4.0/5 (348 download)

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Book Synopsis Mathematics and Computer Science by : Daniele Gardy

Download or read book Mathematics and Computer Science written by Daniele Gardy and published by Birkhäuser. This book was released on 2012-12-06 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book where mathematics and computer science are directly confronted and joined to tackle intricate problems in computer science with deep mathematical approaches. It contains a collection of refereed papers presented at the Colloquium on Mathematics and Computer Science held at the University of Versailles-St-Quentin on September 18-20, 2000. The colloquium was a meeting place for researchers in mathematics and computer science and thus an important opportunity to exchange ideas and points of view, and to present new approaches and new results in the common areas such as algorithms analysis, trees, combinatorics, optimization, performance evaluation and probabilities. The book is intended for a large public in applied mathematics, discrete mathematics and computer science, including researchers, teachers, graduate students and engineers. It provides an overview of the current questions in computer science and related modern mathematical methods. The range of applications is very wide and reaches beyond computer science.

Progress in Pure and Applied Discrete Mathematics, Vol. 1: Probabilistic Methods in Discrete Mathematics

Author : V.F. Kolchin
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3112318986
Total Pages : 480 pages
Book Rating : 4.1/5 (123 download)

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Book Synopsis Progress in Pure and Applied Discrete Mathematics, Vol. 1: Probabilistic Methods in Discrete Mathematics by : V.F. Kolchin

Download or read book Progress in Pure and Applied Discrete Mathematics, Vol. 1: Probabilistic Methods in Discrete Mathematics written by V.F. Kolchin and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-05-18 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: No detailed description available for "Progress in Pure and Applied Discrete Mathematics, Vol. 1: Probabilistic Methods in Discrete Mathematics".

Foundations of Discrete Mathematics with Algorithms and Programming

Author : R. Balakrishnan
Publisher : CRC Press
ISBN 13 : 1351019120
Total Pages : 361 pages
Book Rating : 4.3/5 (51 download)

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Book Synopsis Foundations of Discrete Mathematics with Algorithms and Programming by : R. Balakrishnan

Download or read book Foundations of Discrete Mathematics with Algorithms and Programming written by R. Balakrishnan and published by CRC Press. This book was released on 2018-10-26 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete Mathematics has permeated the whole of mathematics so much so it has now come to be taught even at the high school level. This book presents the basics of Discrete Mathematics and its applications to day-to-day problems in several areas. This book is intended for undergraduate students of Computer Science, Mathematics and Engineering. A number of examples have been given to enhance the understanding of concepts. The programming languages used are Pascal and C.

Probabilistic Analysis of Algorithms

Author : Micha Hofri
Publisher : Springer Science & Business Media
ISBN 13 : 1461248000
Total Pages : 254 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Probabilistic Analysis of Algorithms by : Micha Hofri

Download or read book Probabilistic Analysis of Algorithms written by Micha Hofri and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic Analysis of Algorithms begins with a presentation of the "tools of the trade" currently used in probabilistic analyses, and continues with an applications section in which these tools are used in the analysis ofr selected algorithms. The tools section of the book provides the reader with an arsenal of analytic and numeric computing methods which are then applied to several groups of algorithms to analyze their running time or storage requirements characteristics. Topics covered in the applications section include sorting, communications network protocols and bin packing. While the discussion of the various algorithms is sufficient to motivate their structure, the emphasis throughout is on the probabilistic estimation of their operation under distributional assumptions on their input. Probabilistic Analysis of Algorithms assumes a working knowledge of engineering mathematics, drawing on real and complex analysis, combinatorics and probability theory. While the book is intended primarily as a text for the upper undergraduate and graduate student levels, it contains a wealth of material and should also prove an important reference for researchers. As such it is addressed to computer scientists, mathematicians, operations researchers, and electrical and industrial engineers who are interested in evaluating the probable operation of algorithms, rather than their worst-case behavior.

Methods in Algorithmic Analysis

Author : Vladimir A. Dobrushkin
Publisher : Chapman & Hall/CRC
ISBN 13 : 9781138118041
Total Pages : 824 pages
Book Rating : 4.1/5 (18 download)

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Book Synopsis Methods in Algorithmic Analysis by : Vladimir A. Dobrushkin

Download or read book Methods in Algorithmic Analysis written by Vladimir A. Dobrushkin and published by Chapman & Hall/CRC. This book was released on 2017-06-16 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores the Impact of the Analysis of Algorithms on Many Areas within and beyond Computer Science A flexible, interactive teaching format enhanced by a large selection of examples and exercises Developed from the author's own graduate-level course, Methods in Algorithmic Analysis presents numerous theories, techniques, and methods used for analyzing algorithms. It exposes students to mathematical techniques and methods that are practical and relevant to theoretical aspects of computer science. After introducing basic mathematical and combinatorial methods, the text focuses on various aspects of probability, including finite sets, random variables, distributions, Bayes' theorem, and Chebyshev inequality. It explores the role of recurrences in computer science, numerical analysis, engineering, and discrete mathematics applications. The author then describes the powerful tool of generating functions, which is demonstrated in enumeration problems, such as probabilistic algorithms, compositions and partitions of integers, and shuffling. He also discusses the symbolic method, the principle of inclusion and exclusion, and its applications. The book goes on to show how strings can be manipulated and counted, how the finite state machine and Markov chains can help solve probabilistic and combinatorial problems, how to derive asymptotic results, and how convergence and singularities play leading roles in deducing asymptotic information from generating functions. The final chapter presents the definitions and properties of the mathematical infrastructure needed to accommodate generating functions. Accompanied by more than 1,000 examples and exercises, this comprehensive, classroom-tested text develops students' understanding of the mathematical methodology behind the analysis of algorithms. It emphasizes the important relation between continuous (classical) mathematics and discrete mathematics, which is the basis of computer science.

Concentration of Measure for the Analysis of Randomized Algorithms

Author : Devdatt P. Dubhashi
Publisher : Cambridge University Press
ISBN 13 : 0521884276
Total Pages : 213 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Concentration of Measure for the Analysis of Randomized Algorithms by : Devdatt P. Dubhashi

Download or read book Concentration of Measure for the Analysis of Randomized Algorithms written by Devdatt P. Dubhashi and published by Cambridge University Press. This book was released on 2009-06-15 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a coherent and unified account of classical and more advanced techniques for analyzing the performance of randomized algorithms.

Algorithmics of Nonuniformity

Author : Micha Hofri
Publisher : CRC Press
ISBN 13 : 1498750729
Total Pages : 570 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Algorithmics of Nonuniformity by : Micha Hofri

Download or read book Algorithmics of Nonuniformity written by Micha Hofri and published by CRC Press. This book was released on 2018-07-16 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: Algorithmics of Nonuniformity is a solid presentation about the analysis of algorithms, and the data structures that support them. Traditionally, algorithmics have been approached either via a probabilistic view or an analytic approach. The authors adopt both approaches and bring them together to get the best of both worlds and benefit from the advantage of each approach. The text examines algorithms that are designed to handle general data—sort any array, find the median of any numerical set, and identify patterns in any setting. At the same time, it evaluates "average" performance, "typical" behavior, or in mathematical terms, the expectations of the random variables that describe their operations. Many exercises are presented, which are essential since they convey additional material complementing the content of the chapters. For this reason, the solutions are more than mere answers, but explain and expand upon related concepts, and motivate further work by the reader. Highlights: A unique book that merges probability with analysis of algorithms Approaches analysis of algorithms from the angle of uniformity Non-uniformity makes more realistic models of real-life scenarios possible Results can be applied to many applications Includes many exercises of various levels of difficulty About the Authors: Micha Hofri is a Professor of Computer Science, and former department head at Worcester Polytechnic Institute. He holds a Ph.D. of Industrial Engineering (1972), all from Technion, the Israel Institute of Technology. He has 39 publications in Mathematics. Hosam Mahmoud is a Professor at, the Department of Statistics at George Washington University in Washington D.C., where he used to be the former chair. He holds an Ph.D. in Computer Science from Ohio State University. He is on the editorial board of five academic journals.

Discrete Probability and Algorithms

Author : David Aldous
Publisher : Springer Science & Business Media
ISBN 13 : 1461208017
Total Pages : 169 pages
Book Rating : 4.4/5 (612 download)

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Book Synopsis Discrete Probability and Algorithms by : David Aldous

Download or read book Discrete Probability and Algorithms written by David Aldous and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete probability theory and the theory of algorithms have become close partners over the last ten years, though the roots of this partnership go back much longer. The papers in this volume address the latest developments in this active field. They are from the IMA Workshops "Probability and Algorithms" and "The Finite Markov Chain Renaissance." They represent the current thinking of many of the world's leading experts in the field. Researchers and graduate students in probability, computer science, combinatorics, and optimization theory will all be interested in this collection of articles. The techniques developed and surveyed in this volume are still undergoing rapid development, and many of the articles of the collection offer an expositionally pleasant entree into a research area of growing importance.