Mathematical and Algorithmic Foundations of the Internet

Mathematical and Algorithmic Foundations of the Internet

Author: Fabrizio Luccio

Publisher: CRC Press

Published: 2011-07-06

Total Pages: 224

ISBN-13: 1439831386

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To truly understand how the Internet and Web are organized and function requires knowledge of mathematics and computation theory. Mathematical and Algorithmic Foundations of the Internet introduces the concepts and methods upon which computer networks rely and explores their applications to the Internet and Web. The book offers a unique approach to mathematical and algorithmic concepts, demonstrating their universality by presenting ideas and examples from various fields, including literature, history, and art. Progressing from fundamental concepts to more specific topics and applications, the text covers computational complexity and randomness, networks and graphs, parallel and distributed computing, and search engines. While the mathematical treatment is rigorous, it is presented at a level that can be grasped by readers with an elementary mathematical background. The authors also present a lighter side to this complex subject by illustrating how many of the mathematical concepts have counterparts in everyday life. The book provides in-depth coverage of the mathematical prerequisites and assembles a complete presentation of how computer networks function. It is a useful resource for anyone interested in the inner functioning, design, and organization of the Internet.


The Algorithmic Foundations of Differential Privacy

The Algorithmic Foundations of Differential Privacy

Author: Cynthia Dwork

Publisher:

Published: 2014

Total Pages: 286

ISBN-13: 9781601988188

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The problem of privacy-preserving data analysis has a long history spanning multiple disciplines. As electronic data about individuals becomes increasingly detailed, and as technology enables ever more powerful collection and curation of these data, the need increases for a robust, meaningful, and mathematically rigorous definition of privacy, together with a computationally rich class of algorithms that satisfy this definition. Differential Privacy is such a definition. The Algorithmic Foundations of Differential Privacy starts out by motivating and discussing the meaning of differential privacy, and proceeds to explore the fundamental techniques for achieving differential privacy, and the application of these techniques in creative combinations, using the query-release problem as an ongoing example. A key point is that, by rethinking the computational goal, one can often obtain far better results than would be achieved by methodically replacing each step of a non-private computation with a differentially private implementation. Despite some powerful computational results, there are still fundamental limitations. Virtually all the algorithms discussed herein maintain differential privacy against adversaries of arbitrary computational power -- certain algorithms are computationally intensive, others are efficient. Computational complexity for the adversary and the algorithm are both discussed. The monograph then turns from fundamentals to applications other than query-release, discussing differentially private methods for mechanism design and machine learning. The vast majority of the literature on differentially private algorithms considers a single, static, database that is subject to many analyses. Differential privacy in other models, including distributed databases and computations on data streams, is discussed. The Algorithmic Foundations of Differential Privacy is meant as a thorough introduction to the problems and techniques of differential privacy, and is an invaluable reference for anyone with an interest in the topic.


Modern Discrete Mathematics and Analysis

Modern Discrete Mathematics and Analysis

Author: Nicholas J. Daras

Publisher: Springer

Published: 2018-07-05

Total Pages: 516

ISBN-13: 3319743252

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A variety of modern research in analysis and discrete mathematics is provided in this book along with applications in cryptographic methods and information security, in order to explore new techniques, methods, and problems for further investigation. Distinguished researchers and scientists in analysis and discrete mathematics present their research. Graduate students, scientists and engineers, interested in a broad spectrum of current theories, methods, and applications in interdisciplinary fields will find this book invaluable.


A Guide to Algorithm Design

A Guide to Algorithm Design

Author: Anne Benoit

Publisher: CRC Press

Published: 2013-08-27

Total Pages: 380

ISBN-13: 1439898138

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Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design: Paradigms, Methods, and Complexity Analysis provides a roadmap for readers to determine the difficulty of an algorithmic problem by finding an optimal solution or proving complexity results. It gives a practical treatment of algorithmic complexity and guides readers in solving algorithmic problems. Divided into three parts, the book offers a comprehensive set of problems with solutions as well as in-depth case studies that demonstrate how to assess the complexity of a new problem. Part I helps readers understand the main design principles and design efficient algorithms. Part II covers polynomial reductions from NP-complete problems and approaches that go beyond NP-completeness. Part III supplies readers with tools and techniques to evaluate problem complexity, including how to determine which instances are polynomial and which are NP-hard. Drawing on the authors’ classroom-tested material, this text takes readers step by step through the concepts and methods for analyzing algorithmic complexity. Through many problems and detailed examples, readers can investigate polynomial-time algorithms and NP-completeness and beyond.


Foundations of Algorithms

Foundations of Algorithms

Author: Richard E. Neapolitan

Publisher: Jones & Bartlett Learning

Published: 2011

Total Pages: 647

ISBN-13: 0763782505

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Data Structures & Theory of Computation


The Garbage Collection Handbook

The Garbage Collection Handbook

Author: Richard Jones

Publisher: CRC Press

Published: 2016-09-15

Total Pages: 471

ISBN-13: 1315388006

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Published in 1996, Richard Jones’s Garbage Collection was a milestone in the area of automatic memory management. The field has grown considerably since then, sparking a need for an updated look at the latest state-of-the-art developments. The Garbage Collection Handbook: The Art of Automatic Memory Management brings together a wealth of knowledge gathered by automatic memory management researchers and developers over the past fifty years. The authors compare the most important approaches and state-of-the-art techniques in a single, accessible framework. The book addresses new challenges to garbage collection made by recent advances in hardware and software. It explores the consequences of these changes for designers and implementers of high performance garbage collectors. Along with simple and traditional algorithms, the book covers parallel, incremental, concurrent, and real-time garbage collection. Algorithms and concepts are often described with pseudocode and illustrations. The nearly universal adoption of garbage collection by modern programming languages makes a thorough understanding of this topic essential for any programmer. This authoritative handbook gives expert insight on how different collectors work as well as the various issues currently facing garbage collectors. Armed with this knowledge, programmers can confidently select and configure the many choices of garbage collectors. Web Resource The book’s online bibliographic database at www.gchandbook.org includes over 2,500 garbage collection-related publications. Continually updated, it contains abstracts for some entries and URLs or DOIs for most of the electronically available ones. The database can be searched online or downloaded as BibTeX, PostScript, or PDF. E-book This edition enhances the print version with copious clickable links to algorithms, figures, original papers and definitions of technical terms. In addition, each index entry links back to where it was mentioned in the text, and each entry in the bibliography includes links back to where it was cited.


Foundations of Data Science

Foundations of Data Science

Author: Avrim Blum

Publisher: Cambridge University Press

Published: 2020-01-23

Total Pages: 433

ISBN-13: 1108617360

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This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.


Mathematical Foundations of Computer Networking

Mathematical Foundations of Computer Networking

Author: Srinivasan Keshav

Publisher: Pearson Education

Published: 2012

Total Pages: 496

ISBN-13: 0321792106

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Mathematical techniques pervade current research in computer networking, yet are not taught to most computer science undergraduates. This self-contained, highly-accessible book bridges the gap, providing the mathematical grounding students and professionals need to successfully design or evaluate networking systems. The only book of its kind, it brings together information previously scattered amongst multiple texts. It first provides crucial background in basic mathematical tools, and then illuminates the specific theories that underlie computer networking. Coverage includes: * Basic probability * Statistics * Linear Algebra * Optimization * Signals, Systems, and Transforms, including Fourier series and transforms, Laplace transforms, DFT, FFT, and Z transforms * Queuing theory * Game Theory * Control theory * Information theory


Algorithms and Complexity

Algorithms and Complexity

Author: Herbert S. Wilf

Publisher: A K PETERS

Published: 2020-09-30

Total Pages: 219

ISBN-13: 9780367659486

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This book is an introductory textbook on the design and analysis of algorithms. The author uses a careful selection of a few topics to illustrate the tools for algorithm analysis. Recursive algorithms are illustrated by Quicksort, FFT, fast matrix multiplications, and others. Algorithms associated with the network flow problem are fundamental in many areas of graph connectivity, matching theory, etc. Algorithms in number theory are discussed with some applications to public key encryption. This second edition will differ from the present edition mainly in that solutions to most of the exercises will be included.


The Power of Algorithms

The Power of Algorithms

Author: Giorgio Ausiello

Publisher: Springer Science & Business Media

Published: 2013-11-08

Total Pages: 262

ISBN-13: 3642396526

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To examine, analyze, and manipulate a problem to the point of designing an algorithm for solving it is an exercise of fundamental value in many fields. With so many everyday activities governed by algorithmic principles, the power, precision, reliability and speed of execution demanded by users have transformed the design and construction of algorithms from a creative, artisanal activity into a full-fledged science in its own right. This book is aimed at all those who exploit the results of this new science, as designers and as consumers. The first chapter is an overview of the related history, demonstrating the long development of ideas such as recursion and more recent formalizations such as computability. The second chapter shows how the design of algorithms requires appropriate techniques and sophisticated organization of data. In the subsequent chapters the contributing authors present examples from diverse areas – such as routing and networking problems, Web search, information security, auctions and games, complexity and randomness, and the life sciences – that show how algorithmic thinking offers practical solutions and also deepens domain knowledge. The contributing authors are top-class researchers with considerable academic and industrial experience; they are also excellent educators and communicators and they draw on this experience with enthusiasm and humor. This book is an excellent introduction to an intriguing domain and it will be enjoyed by undergraduate and postgraduate students in computer science, engineering, and mathematics, and more broadly by all those engaged with algorithmic thinking.