Beyond The Worst Case Analysis Of Algorithms
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Beyond The Worst Case Analysis Of Algorithms
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Author : Tim Roughgarden
language : en
Publisher: Cambridge University Press
Release Date : 2021-01-14
Beyond The Worst Case Analysis Of Algorithms written by Tim Roughgarden and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-14 with Computers categories.
Introduces exciting new methods for assessing algorithms for problems ranging from clustering to linear programming to neural networks.
Analysis Of Algorithms
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Author : Jeffrey J. McConnell
language : en
Publisher: Jones & Bartlett Learning
Release Date : 2008
Analysis Of Algorithms written by Jeffrey J. McConnell and has been published by Jones & Bartlett Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
Data Structures & Theory of Computation
Average Case Analysis Of Algorithms On Sequences
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Author : Wojciech Szpankowski
language : en
Publisher: John Wiley & Sons
Release Date : 2011-10-14
Average Case Analysis Of Algorithms On Sequences written by Wojciech Szpankowski and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-14 with Mathematics categories.
A timely book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications, most notably in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms, combining both analytical and probabilistic tools in a single volume. * Tools are illustrated through problems on words with applications to molecular biology, data compression, security, and pattern matching. * Includes chapters on algorithms and data structures on words, probabilistic and analytical models, inclusion-exclusion principles, first and second moment methods, subadditive ergodic theorem and large deviations, elements of information theory, generating functions, complex asymptotic methods, Mellin transform and its applications, and analytic poissonization and depoissonization. * Written by an established researcher with a strong international reputation in the field.
Practical Analysis Of Algorithms
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Author : Dana Vrajitoru
language : en
Publisher: Springer
Release Date : 2014-09-03
Practical Analysis Of Algorithms written by Dana Vrajitoru and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-03 with Computers categories.
This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Features: includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background; describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations; examines recurrence relations; discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities; reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort; introduces a variety of classical finite graph algorithms, together with an analysis of their complexity; provides an appendix on probability theory, reviewing the major definitions and theorems used in the book.
An Introduction To The Analysis Of Algorithms
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Author : Robert Sedgewick
language : en
Publisher: Addison-Wesley
Release Date : 2013-01-18
An Introduction To The Analysis Of Algorithms written by Robert Sedgewick and has been published by Addison-Wesley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-18 with Computers categories.
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
Twenty Lectures On Algorithmic Game Theory
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Author : Tim Roughgarden
language : en
Publisher: Cambridge University Press
Release Date : 2016-09-01
Twenty Lectures On Algorithmic Game Theory written by Tim Roughgarden and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-01 with Computers categories.
Computer science and economics have engaged in a lively interaction over the past fifteen years, resulting in the new field of algorithmic game theory. Many problems that are central to modern computer science, ranging from resource allocation in large networks to online advertising, involve interactions between multiple self-interested parties. Economics and game theory offer a host of useful models and definitions to reason about such problems. The flow of ideas also travels in the other direction, and concepts from computer science are increasingly important in economics. This book grew out of the author's Stanford University course on algorithmic game theory, and aims to give students and other newcomers a quick and accessible introduction to many of the most important concepts in the field. The book also includes case studies on online advertising, wireless spectrum auctions, kidney exchange, and network management.
Design And Analysis Of Algorithms
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Author : Parag H. Dave
language : en
Publisher: Pearson Education India
Release Date : 2007-09
Design And Analysis Of Algorithms written by Parag H. Dave and has been published by Pearson Education India this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09 with Computers categories.
"All aspects pertaining to algorithm design and algorithm analysis have been discussed over the chapters in this book-- Design and Analysis of Algorithms"--Resource description page.
Bandit Algorithms
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Author : Tor Lattimore
language : en
Publisher: Cambridge University Press
Release Date : 2020-07-16
Bandit Algorithms written by Tor Lattimore and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-16 with Business & Economics categories.
A comprehensive and rigorous introduction for graduate students and researchers, with applications in sequential decision-making problems.
Data Structures And Algorithm Analysis In C
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Author : Mark Allen Weiss
language : en
Publisher:
Release Date : 2003
Data Structures And Algorithm Analysis In C written by Mark Allen Weiss and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with C++ (Computer program language) categories.
In this second edition of his successful book, experienced teacher and author Mark Allen Weiss continues to refine and enhance his innovative approach to algorithms and data structures. Written for the advanced data structures course, this text highlights theoretical topics such as abstract data types and the efficiency of algorithms, as well as performance and running time. Before covering algorithms and data structures, the author provides a brief introduction to C++ for programmers unfamiliar with the language. Dr Weiss's clear writing style, logical organization of topics, and extensive use of figures and examples to demonstrate the successive stages of an algorithm make this an accessible, valuable text. New to this Edition *An appendix on the Standard Template Library (STL) *C++ code, tested on multiple platforms, that conforms to the ANSI ISO final draft standard 0201361221B04062001
Fundamentals Of The Average Case Analysis Of Particular Algorithms
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Author : Rainer Kemp
language : en
Publisher: Wiley
Release Date : 1985-04-04
Fundamentals Of The Average Case Analysis Of Particular Algorithms written by Rainer Kemp and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985-04-04 with Computers categories.
A careful and cogent analysis of the average-case behavior of a variety of algorithms accompanied by mathematical calculations. The analysis consists of determining the behavior of an algorithm in the best, worst, and average case. Material is outlined in various exercises and problems.