Author: Thomas H. Cormen

Publisher: MIT Press

ISBN: 0262033844

Category: Computers

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### Introduction to Algorithms

A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow.

### Algorithms Unlocked

Have you ever wondered how your GPS can find the fastest way to your destination, selecting one route from seemingly countless possibilities in mere seconds? How your credit card account number is protected when you make a purchase over the Internet? The answer is algorithms. And how do these mathematical formulations translate themselves into your GPS, your laptop, or your smart phone? This book offers an engagingly written guide to the basics of computer algorithms. In Algorithms Unlocked, Thomas Cormen -- coauthor of the leading college textbook on the subject -- provides a general explanation, with limited mathematics, of how algorithms enable computers to solve problems. Readers will learn what computer algorithms are, how to describe them, and how to evaluate them. They will discover simple ways to search for information in a computer; methods for rearranging information in a computer into a prescribed order ("sorting"); how to solve basic problems that can be modeled in a computer with a mathematical structure called a "graph" (useful for modeling road networks, dependencies among tasks, and financial relationships); how to solve problems that ask questions about strings of characters such as DNA structures; the basic principles behind cryptography; fundamentals of data compression; and even that there are some problems that no one has figured out how to solve on a computer in a reasonable amount of time.

### Introduction to Algorithms

This book emphasizes the creative aspects of algorithm design by examining steps used in the process of algorithm development. The heart of the creative process lies in an analogy between proving mathematical theorems by induction and designing combinatorial algorithms. The book contains hundreds of problems and examples. It is designed to enhance the reader's problem-solving abilities and understanding of the principles behind algorithm design. 0201120372B04062001

### Instructor's Manual to Accompany Introduction to Algorithms

### An Introduction to the Analysis of Algorithms

Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code An all-new chapter introducing analytic combinatorics Simplified derivations via analytic combinatorics throughout The book’s thorough, self-contained coverage will help readers appreciate the field’s challenges, prepare them for advanced results—covered in their monograph Analytic Combinatorics and in Donald Knuth’s The Art of Computer Programming books—and provide the background they need to keep abreast of new research. "[Sedgewick and Flajolet] are not only worldwide leaders of the field, they also are masters of exposition. I am sure that every serious computer scientist will find this book rewarding in many ways." —From the Foreword by Donald E. Knuth

### An Introduction to Bioinformatics Algorithms

Algorithms and Complexity. Molecular Biology Primer. Exhaustive Search. Greedy Algorithms. Dynamic Programming Algorithms. Divide-and-Conquer Algorithms. Graph Algorithms. Combinatorial Pattern Matching. Clustering and Trees. Hidden Markov Models. Randomized Algorithms.

### The Algorithm Design Manual

This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java

### Introduction to Parallel Algorithms

Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest. This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject exist. It features a systematic approach to the latest design techniques, providing analysis and implementation details for each parallel algorithm described in the book. Introduction to Parallel Algorithms covers foundations of parallel computing; parallel algorithms for trees and graphs; parallel algorithms for sorting, searching, and merging; and numerical algorithms. This remarkable book: * Presents basic concepts in clear and simple terms * Incorporates numerous examples to enhance students' understanding * Shows how to develop parallel algorithms for all classical problems in computer science, mathematics, and engineering * Employs extensive illustrations of new design techniques * Discusses parallel algorithms in the context of PRAM model * Includes end-of-chapter exercises and detailed references on parallel computing. This book enables universities to offer parallel algorithm courses at the senior undergraduate level in computer science and engineering. It is also an invaluable text/reference for graduate students, scientists, and engineers in computer science, mathematics, and engineering.

### A Concise and Practical Introduction to Programming Algorithms in Java

A Concise and Practical Introduction to Programming Algorithms in Java has two main goals. The first is for novice programmers to learn progressively the basic concepts underlying most imperative programming languages using Java. The second goal is to introduce new programmers to the very basic principles of thinking the algorithmic way and turning the algorithms into programs using the programming concepts of Java. The book is divided into two parts and includes: The fundamental notions of variables, expressions and assignments with type checking - Conditional and loop statements - Explanation of the concepts of functions with pass-by-value arguments and recursion - Fundamental sequential and bisection search techniques - Basic iterative and recursive sorting algorithms. Each chapter of the book concludes with a set of exercises to enable students to practice concepts covered.

### Mathematics of Big Data

The first book to present the common mathematical foundations of big data analysis across a range of applications and technologies. Today, the volume, velocity, and variety of data are increasing rapidly across a range of fields, including Internet search, healthcare, finance, social media, wireless devices, and cybersecurity. Indeed, these data are growing at a rate beyond our capacity to analyze them. The tools—including spreadsheets, databases, matrices, and graphs—developed to address this challenge all reflect the need to store and operate on data as whole sets rather than as individual elements. This book presents the common mathematical foundations of these data sets that apply across many applications and technologies. Associative arrays unify and simplify data, allowing readers to look past the differences among the various tools and leverage their mathematical similarities in order to solve the hardest big data challenges. The book first introduces the concept of the associative array in practical terms, presents the associative array manipulation system D4M (Dynamic Distributed Dimensional Data Model), and describes the application of associative arrays to graph analysis and machine learning. It provides a mathematically rigorous definition of associative arrays and describes the properties of associative arrays that arise from this definition. Finally, the book shows how concepts of linearity can be extended to encompass associative arrays. Mathematics of Big Data can be used as a textbook or reference by engineers, scientists, mathematicians, computer scientists, and software engineers who analyze big data.

### Understanding Machine Learning

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

### Introduction to Algorithms and Numerical Methods

### Introduction to Algorithms

Facts101 is your complete guide to Introduction to Algorithms. In this book, you will learn topics such as as those in your book plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

### Real-World Algorithms

An introduction to algorithms for readers with no background in advanced mathematics or computer science, emphasizing examples and real-world problems.

### Introduction to the Design and Analysis of Algorithms

Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, 'Introduction to the Design and Analysis of Algorithms' presents the subject in a coherent and innovative manner.

### Introduction to computing and algorithms

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Author: Thomas H. Cormen

Publisher: MIT Press

ISBN: 0262033844

Category: Computers

Page: 1292

View: 8281

Author: Thomas H. Cormen

Publisher: MIT Press

ISBN: 0262313235

Category: Computers

Page: 240

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*A Creative Approach*

Author: Udi Manber

Publisher: Addison Wesley

ISBN: 9780201120370

Category: Computers

Page: 478

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Author: Julie Sussman

Publisher: N.A

ISBN: N.A

Category: Algorithms

Page: 260

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Author: Robert Sedgewick,Philippe Flajolet

Publisher: Addison-Wesley

ISBN: 0133373487

Category: Computers

Page: 604

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Author: Neil C. Jones,Pavel A. Pevzner,Pavel Pevzner

Publisher: MIT Press

ISBN: 9780262101066

Category: Computers

Page: 435

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Author: Steven S Skiena

Publisher: Springer Science & Business Media

ISBN: 1848000707

Category: Computers

Page: 730

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Author: C. Xavier,S. S. Iyengar

Publisher: John Wiley & Sons

ISBN: 9780471251828

Category: Computers

Page: 365

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Author: Frank Nielsen

Publisher: Springer Science & Business Media

ISBN: 9781848823396

Category: Computers

Page: 252

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*Spreadsheets, Databases, Matrices, and Graphs*

Author: Jeremy Kepner,Hayden Jananthan

Publisher: MIT Press

ISBN: 0262347911

Category: Computers

Page: 448

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*From Theory to Algorithms*

Author: Shai Shalev-Shwartz,Shai Ben-David

Publisher: Cambridge University Press

ISBN: 1107057132

Category: Computers

Page: 409

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Author: Brice Carnahan,James O. Wilkes

Publisher: N.A

ISBN: N.A

Category: Algorithms

Page: N.A

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*Mathematics, Mathematics*

Author: CTI Reviews

Publisher: Cram101 Textbook Reviews

ISBN: 1478414642

Category: Education

Page: 438

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*A Beginner's Guide*

Author: Panos Louridas

Publisher: MIT Press

ISBN: 0262035707

Category: Computers

Page: 528

View: 980

Author: Anany Levitin

Publisher: Pearson Education

ISBN: 9780273764113

Category: Juvenile Nonfiction

Page: 589

View: 7468

Author: Russell L. Shackelford

Publisher: Prentice Hall

ISBN: 9780201636130

Category: Computers

Page: 434

View: 2878