Probability And Computing

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Probability and Computing

Author : Michael Mitzenmacher
Publisher : Cambridge University Press
ISBN 13 : 9780521835404
Total Pages : 372 pages
Book Rating : 4.8/5 (354 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.

Probability and Computing

Author : Michael Mitzenmacher
Publisher : Cambridge University Press
ISBN 13 : 110715488X
Total Pages : 489 pages
Book Rating : 4.1/5 (71 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 2017-07-03 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: This greatly expanded new edition offers a comprehensive introduction to randomization and probabilistic techniques in modern computer science.

Probability, Statistics, and Queueing Theory

Author : Arnold O. Allen
Publisher : Academic Press
ISBN 13 : 0080571050
Total Pages : 768 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Probability, Statistics, and Queueing Theory by : Arnold O. Allen

Download or read book Probability, Statistics, and Queueing Theory written by Arnold O. Allen and published by Academic Press. This book was released on 2014-06-28 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a textbook on applied probability and statistics with computer science applications for students at the upper undergraduate level. It may also be used as a self study book for the practicing computer science professional. The successful first edition of this book proved extremely useful to students who need to use probability, statistics and queueing theory to solve problems in other fields, such as engineering, physics, operations research, and management science. The book has also been successfully used for courses in queueing theory for operations research students. This second edition includes a new chapter on regression as well as more than twice as many exercises at the end of each chapter. While the emphasis is the same as in the first edition, this new book makes more extensive use of available personal computer software, such as Minitab and Mathematica.

Probability and Statistics for Computer Science

Author : James L. Johnson
Publisher : John Wiley & Sons
ISBN 13 : 1118165969
Total Pages : 764 pages
Book Rating : 4.1/5 (181 download)

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Book Synopsis Probability and Statistics for Computer Science by : James L. Johnson

Download or read book Probability and Statistics for Computer Science written by James L. Johnson and published by John Wiley & Sons. This book was released on 2011-09-09 with total page 764 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive and thorough development of both probability and statistics for serious computer scientists; goal-oriented: "to present the mathematical analysis underlying probability results" Special emphases on simulation and discrete decision theory Mathematically-rich, but self-contained text, at a gentle pace Review of calculus and linear algebra in an appendix Mathematical interludes (in each chapter) which examine mathematical techniques in the context of probabilistic or statistical importance Numerous section exercises, summaries, historical notes, and Further Readings for reinforcement of content

Probability and Statistics for the Engineering, Computing, and Physical Sciences

Author : Edward R. Dougherty
Publisher :
ISBN 13 :
Total Pages : 824 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Probability and Statistics for the Engineering, Computing, and Physical Sciences by : Edward R. Dougherty

Download or read book Probability and Statistics for the Engineering, Computing, and Physical Sciences written by Edward R. Dougherty and published by . This book was released on 1990 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Randomized Algorithms

Author : Rajeev Motwani
Publisher : Cambridge University Press
ISBN 13 : 9780521474658
Total Pages : 496 pages
Book Rating : 4.4/5 (746 download)

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Book Synopsis Randomized Algorithms by : Rajeev Motwani

Download or read book Randomized Algorithms written by Rajeev Motwani and published by Cambridge University Press. This book was released on 1995-08-25 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents basic tools from probability theory used in algorithmic applications, with concrete examples.

Probability and Statistics for Computer Scientists

Author : Michael Baron
Publisher : CRC Press
ISBN 13 : 1498760600
Total Pages : 475 pages
Book Rating : 4.4/5 (987 download)

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Book Synopsis Probability and Statistics for Computer Scientists by : Michael Baron

Download or read book Probability and Statistics for Computer Scientists written by Michael Baron and published by CRC Press. This book was released on 2013-08-05 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling ToolsIncorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make o

Probability and Algorithms

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309047765
Total Pages : 189 pages
Book Rating : 4.3/5 (9 download)

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Book Synopsis Probability and Algorithms by : National Research Council

Download or read book Probability and Algorithms written by National Research Council and published by National Academies Press. This book was released on 1992-02-01 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: Some of the hardest computational problems have been successfully attacked through the use of probabilistic algorithms, which have an element of randomness to them. Concepts from the field of probability are also increasingly useful in analyzing the performance of algorithms, broadening our understanding beyond that provided by the worst-case or average-case analyses. This book surveys both of these emerging areas on the interface of the mathematical sciences and computer science. It is designed to attract new researchers to this area and provide them with enough background to begin explorations of their own.

Fuzzy Probability and Statistics

Author : James J. Buckley
Publisher : Springer
ISBN 13 : 3540331905
Total Pages : 270 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Fuzzy Probability and Statistics by : James J. Buckley

Download or read book Fuzzy Probability and Statistics written by James J. Buckley and published by Springer. This book was released on 2008-09-12 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book combines material from our previous books FP (Fuzzy Probabilities: New Approach and Applications,Physica-Verlag, 2003) and FS (Fuzzy Statistics, Springer, 2004), plus has about one third new results. From FP we have material on basic fuzzy probability, discrete (fuzzy Poisson,binomial) and continuous (uniform, normal, exponential) fuzzy random variables. From FS we included chapters on fuzzy estimation and fuzzy hypothesis testing related to means, variances, proportions, correlation and regression. New material includes fuzzy estimators for arrival and service rates, and the uniform distribution, with applications in fuzzy queuing theory. Also, new to this book, is three chapters on fuzzy maximum entropy (imprecise side conditions) estimators producing fuzzy distributions and crisp discrete/continuous distributions. Other new results are: (1) two chapters on fuzzy ANOVA (one-way and two-way); (2) random fuzzy numbers with applications to fuzzy Monte Carlo studies; and (3) a fuzzy nonparametric estimator for the median.

Numerical Issues in Statistical Computing for the Social Scientist

Author : Micah Altman
Publisher : John Wiley & Sons
ISBN 13 : 0471475742
Total Pages : 323 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Numerical Issues in Statistical Computing for the Social Scientist by : Micah Altman

Download or read book Numerical Issues in Statistical Computing for the Social Scientist written by Micah Altman and published by John Wiley & Sons. This book was released on 2004-02-15 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: At last—a social scientist's guide through the pitfalls ofmodern statistical computing Addressing the current deficiency in the literature onstatistical methods as they apply to the social and behavioralsciences, Numerical Issues in Statistical Computing for the SocialScientist seeks to provide readers with a unique practicalguidebook to the numerical methods underlying computerizedstatistical calculations specific to these fields. The authorsdemonstrate that knowledge of these numerical methods and how theyare used in statistical packages is essential for making accurateinferences. With the aid of key contributors from both the socialand behavioral sciences, the authors have assembled a rich set ofinterrelated chapters designed to guide empirical social scientiststhrough the potential minefield of modern statisticalcomputing. Uniquely accessible and abounding in modern-day tools, tricks,and advice, the text successfully bridges the gap between thecurrent level of social science methodology and the moresophisticated technical coverage usually associated with thestatistical field. Highlights include: A focus on problems occurring in maximum likelihoodestimation Integrated examples of statistical computing (using softwarepackages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS,WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensivestatistical approaches such as ecological inference, Markov chainMonte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statisticalprocedures, and their applications in the field Replications and re-analysis of published social scienceresearch, using innovative numerical methods Key numerical estimation issues along with the means ofavoiding common pitfalls A related Web site includes test data for use in demonstratingnumerical problems, code for applying the original methodsdescribed in the book, and an online bibliography of Web resourcesfor the statistical computation Designed as an independent research tool, a professionalreference, or a classroom supplement, the book presents awell-thought-out treatment of a complex and multifaceted field.

Probability and Statistics for Computer Science

Author : David Forsyth
Publisher : Springer
ISBN 13 : 3319644106
Total Pages : 367 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis Probability and Statistics for Computer Science by : David Forsyth

Download or read book Probability and Statistics for Computer Science written by David Forsyth and published by Springer. This book was released on 2017-12-13 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is aimed at computer science undergraduates late in sophomore or early in junior year, supplying a comprehensive background in qualitative and quantitative data analysis, probability, random variables, and statistical methods, including machine learning. With careful treatment of topics that fill the curricular needs for the course, Probability and Statistics for Computer Science features: • A treatment of random variables and expectations dealing primarily with the discrete case. • A practical treatment of simulation, showing how many interesting probabilities and expectations can be extracted, with particular emphasis on Markov chains. • A clear but crisp account of simple point inference strategies (maximum likelihood; Bayesian inference) in simple contexts. This is extended to cover some confidence intervals, samples and populations for random sampling with replacement, and the simplest hypothesis testing. • A chapter dealing with classification, explaining why it’s useful; how to train SVM classifiers with stochastic gradient descent; and how to use implementations of more advanced methods such as random forests and nearest neighbors. • A chapter dealing with regression, explaining how to set up, use and understand linear regression and nearest neighbors regression in practical problems. • A chapter dealing with principal components analysis, developing intuition carefully, and including numerous practical examples. There is a brief description of multivariate scaling via principal coordinate analysis. • A chapter dealing with clustering via agglomerative methods and k-means, showing how to build vector quantized features for complex signals. Illustrated throughout, each main chapter includes many worked examples and other pedagogical elements such as boxed Procedures, Definitions, Useful Facts, and Remember This (short tips). Problems and Programming Exercises are at the end of each chapter, with a summary of what the reader should know. Instructor resources include a full set of model solutions for all problems, and an Instructor's Manual with accompanying presentation slides.

Computational Probability

Author : John H. Drew
Publisher : Springer
ISBN 13 : 3319433237
Total Pages : 336 pages
Book Rating : 4.3/5 (194 download)

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Book Synopsis Computational Probability by : John H. Drew

Download or read book Computational Probability written by John H. Drew and published by Springer. This book was released on 2016-12-15 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new edition includes the latest advances and developments in computational probability involving A Probability Programming Language (APPL). The book examines and presents, in a systematic manner, computational probability methods that encompass data structures and algorithms. The developed techniques address problems that require exact probability calculations, many of which have been considered intractable in the past. The book addresses the plight of the probabilist by providing algorithms to perform calculations associated with random variables. Computational Probability: Algorithms and Applications in the Mathematical Sciences, 2nd Edition begins with an introductory chapter that contains short examples involving the elementary use of APPL. Chapter 2 reviews the Maple data structures and functions necessary to implement APPL. This is followed by a discussion of the development of the data structures and algorithms (Chapters 3–6 for continuous random variables and Chapters 7–9 for discrete random variables) used in APPL. The book concludes with Chapters 10–15 introducing a sampling of various applications in the mathematical sciences. This book should appeal to researchers in the mathematical sciences with an interest in applied probability and instructors using the book for a special topics course in computational probability taught in a mathematics, statistics, operations research, management science, or industrial engineering department.

Probability and Statistics in the Engineering and Computing Sciences

Author : Janet Susan Milton
Publisher : McGraw-Hill Science, Engineering & Mathematics
ISBN 13 :
Total Pages : 754 pages
Book Rating : 4.:/5 (51 download)

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Book Synopsis Probability and Statistics in the Engineering and Computing Sciences by : Janet Susan Milton

Download or read book Probability and Statistics in the Engineering and Computing Sciences written by Janet Susan Milton and published by McGraw-Hill Science, Engineering & Mathematics. This book was released on 1986 with total page 754 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Introduction to Probability

Author : David F. Anderson
Publisher : Cambridge University Press
ISBN 13 : 110824498X
Total Pages : 447 pages
Book Rating : 4.1/5 (82 download)

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Book Synopsis Introduction to Probability by : David F. Anderson

Download or read book Introduction to Probability written by David F. Anderson and published by Cambridge University Press. This book was released on 2017-11-02 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classroom-tested textbook is an introduction to probability theory, with the right balance between mathematical precision, probabilistic intuition, and concrete applications. Introduction to Probability covers the material precisely, while avoiding excessive technical details. After introducing the basic vocabulary of randomness, including events, probabilities, and random variables, the text offers the reader a first glimpse of the major theorems of the subject: the law of large numbers and the central limit theorem. The important probability distributions are introduced organically as they arise from applications. The discrete and continuous sides of probability are treated together to emphasize their similarities. Intended for students with a calculus background, the text teaches not only the nuts and bolts of probability theory and how to solve specific problems, but also why the methods of solution work.

Probability Models for Computer Science

Author : Sheldon M. Ross
Publisher : Taylor & Francis US
ISBN 13 : 9780125980517
Total Pages : 304 pages
Book Rating : 4.9/5 (85 download)

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Book Synopsis Probability Models for Computer Science by : Sheldon M. Ross

Download or read book Probability Models for Computer Science written by Sheldon M. Ross and published by Taylor & Francis US. This book was released on 2002 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: The role of probability in computer science has been growing for years and, in lieu of a tailored textbook, many courses have employed a variety of similar, but not entirely applicable, alternatives. To meet the needs of the computer science graduate student (and the advanced undergraduate), best-selling author Sheldon Ross has developed the premier probability text for aspiring computer scientists involved in computer simulation and modeling. The math is precise and easily understood. As with his other texts, Sheldon Ross presents very clear explanations of concepts and covers those probability models that are most in demand by, and applicable to, computer science and related majors and practitioners. Many interesting examples and exercises have been chosen to illuminate the techniques presented Examples relating to bin packing, sorting algorithms, the find algorithm, random graphs, self-organising list problems, the maximum weighted independent set problem, hashing, probabilistic verification, max SAT problem, queuing networks, distributed workload models, and many othersMany interesting examples and exercises have been chosen to illuminate the techniques presented

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.

Probabilistic Methods for Algorithmic Discrete Mathematics

Author : Michel Habib
Publisher : Springer Science & Business Media
ISBN 13 : 9783540646228
Total Pages : 346 pages
Book Rating : 4.6/5 (462 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 1998-08-19 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book gives an accessible account of modern pro- babilistic methods for analyzing combinatorial structures and algorithms. Each topic is approached in a didactic manner but the most recent developments are linked to the basic ma- terial. Extensive lists of references and a detailed index will make this a useful guide for graduate students and researchers. Special features included: - a simple treatment of Talagrand inequalities and their applications - an overview and many carefully worked out examples of the probabilistic analysis of combinatorial algorithms - a discussion of the "exact simulation" algorithm (in the context of Markov Chain Monte Carlo Methods) - a general method for finding asymptotically optimal or near optimal graph colouring, showing how the probabilistic method may be fine-tuned to explit the structure of the underlying graph - a succinct treatment of randomized algorithms and derandomization techniques