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1Linear Programming : An Introduction To Finite Improvement Algorithms

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  • Title: ➤  Linear Programming : An Introduction To Finite Improvement Algorithms
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The book is available for download in "texts" format, the size of the file-s is: 897.54 Mbs, the file-s for this book were downloaded 116 times, the file-s went public at Tue Nov 23 2021.

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2Introduction To Algorithms, Third Edition ( PDFDrive ) ( 1)

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The book is available for download in "texts" format, the size of the file-s is: 544.20 Mbs, the file-s for this book were downloaded 338 times, the file-s went public at Fri Feb 19 2021.

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3Introduction To Computing And Algorithms

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The book is available for download in "texts" format, the size of the file-s is: 940.20 Mbs, the file-s for this book were downloaded 103 times, the file-s went public at Wed Nov 20 2019.

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4Python. An Introduction To Programming ( Chapter 10 Basic Algorithms)

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Python. An Introduction To Programming ( Chapter 10 Basic Algorithms)

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The book is available for download in "texts" format, the size of the file-s is: 23.67 Mbs, the file-s for this book were downloaded 35 times, the file-s went public at Mon May 06 2024.

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5Computer Algorithms: Introduction To Design And Analysis

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The book is available for download in "texts" format, the size of the file-s is: 649.48 Mbs, the file-s for this book were downloaded 22 times, the file-s went public at Thu Feb 20 2020.

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6Introduction To Quantum Algorithms: The Basics

Speaker: Michele Mosca Date: May 2002

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The book is available for download in "movies" format, the size of the file-s is: 2391.22 Mbs, the file-s for this book were downloaded 665 times, the file-s went public at Wed Feb 18 2004.

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7MIT 6.006 Introduction To Algorithms, Spring 2020

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Instructor: Prof. Erik Demaine, Dr. Jason Ku, Prof. Justin Solomon View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY *NOTE: Problem Session 6 is unavailable.* This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments .

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8Introduction To Mathematical Programming Applications And Algorithms (for Windows)

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Instructor: Prof. Erik Demaine, Dr. Jason Ku, Prof. Justin Solomon View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY *NOTE: Problem Session 6 is unavailable.* This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments .

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The book is available for download in "texts" format, the size of the file-s is: 1776.41 Mbs, the file-s for this book were downloaded 15 times, the file-s went public at Mon Apr 03 2023.

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9Introduction To Algorithms In Pascal

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Instructor: Prof. Erik Demaine, Dr. Jason Ku, Prof. Justin Solomon View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY *NOTE: Problem Session 6 is unavailable.* This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments .

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The book is available for download in "texts" format, the size of the file-s is: 992.82 Mbs, the file-s for this book were downloaded 367 times, the file-s went public at Mon Jun 11 2018.

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10Computer Algorithms : Introduction To Design And Analysis

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Instructor: Prof. Erik Demaine, Dr. Jason Ku, Prof. Justin Solomon View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY *NOTE: Problem Session 6 is unavailable.* This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments .

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The book is available for download in "texts" format, the size of the file-s is: 1274.54 Mbs, the file-s for this book were downloaded 759 times, the file-s went public at Thu Sep 27 2018.

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11Introduction To Parallel Computing : Design And Analysis Of Algorithms

Instructor: Prof. Erik Demaine, Dr. Jason Ku, Prof. Justin Solomon View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY *NOTE: Problem Session 6 is unavailable.* This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments .

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  • Title: ➤  Introduction To Parallel Computing : Design And Analysis Of Algorithms
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The book is available for download in "texts" format, the size of the file-s is: 1076.28 Mbs, the file-s for this book were downloaded 158 times, the file-s went public at Fri Oct 15 2021.

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12An Introduction To Quantum Computing Algorithms

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Instructor: Prof. Erik Demaine, Dr. Jason Ku, Prof. Justin Solomon View the complete course: https://ocw.mit.edu/6-006S20 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP63EdVPNLG3ToM6LaEUuStEY *NOTE: Problem Session 6 is unavailable.* This course is an introduction to mathematical modeling of computational problems, as well as common algorithms, algorithmic paradigms, and data structures used to solve these problems. It emphasizes the relationship between algorithms and programming and introduces basic performance measures and analysis techniques for these problems. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu Support OCW at http://ow.ly/a1If50zVRlQ We encourage constructive comments and discussion on OCW’s YouTube and other social media channels. Personal attacks, hate speech, trolling, and inappropriate comments are not allowed and may be removed. More details at https://ocw.mit.edu/comments .

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The book is available for download in "texts" format, the size of the file-s is: 318.54 Mbs, the file-s for this book were downloaded 159 times, the file-s went public at Tue Sep 03 2019.

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13Introduction To Algorithms Third Edition ( 2009)

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The latest 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. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor.  Introduction to Algorithms  uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called "Divide-and-Conquer"), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.

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The book is available for download in "texts" format, the size of the file-s is: 542.49 Mbs, the file-s for this book were downloaded 29313 times, the file-s went public at Thu Jan 11 2024.

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14Introduction To Genetic Algorithms

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The latest 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. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor.  Introduction to Algorithms  uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called "Divide-and-Conquer"), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.

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The book is available for download in "texts" format, the size of the file-s is: 1067.63 Mbs, the file-s for this book were downloaded 85 times, the file-s went public at Mon Nov 29 2021.

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15An Introduction To The General Theory Of Algorithms

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The latest 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. Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor.  Introduction to Algorithms  uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor. The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called "Divide-and-Conquer"), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many exercises and problems have been added for this edition. The international paperback edition is no longer available; the hardcover is available worldwide.

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The book is available for download in "texts" format, the size of the file-s is: 405.32 Mbs, the file-s for this book were downloaded 1160 times, the file-s went public at Fri Dec 09 2011.

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16Solutions For Introduction To Algorithms CLRS

Solutions for Introduction to Algorithms(manesht)

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The book is available for download in "data" format, the size of the file-s is: 0.21 Mbs, the file-s for this book were downloaded 7994 times, the file-s went public at Sun Aug 01 2010.

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17Introduction To Monte Carlo Algorithms

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In these lectures, given in '96 summer schools in Beg-Rohu (France) and Budapest, I discuss the fundamental principles of thermodynamic and dynamic Monte Carlo methods in a simple light-weight fashion. The keywords are MARKOV CHAINS, SAMPLING, DETAILED BALANCE, A PRIORI PROBABILITIES, REJECTIONS, ERGODICITY, "FASTER THAN THE CLOCK ALGORITHMS". The emphasis is on ORIENTATION, which is difficult to obtain (all the mathematics being simple). A firm sense of orientation helps to avoid getting lost, especially if you want to leave safe trodden-out paths established by common usage. Even though I remain quite basic (and, I hope, readable), I make every effort to drive home the essential messages, which are easily explained: the crystal-clearness of detail balance, the main problem with Markov chains, the great algorithmic freedom, both in thermodynamic and dynamic Monte Carlo, and the fundamental differences between the two problems.

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The book is available for download in "texts" format, the size of the file-s is: 17.00 Mbs, the file-s for this book were downloaded 160 times, the file-s went public at Sun Sep 22 2013.

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182. Introduction To Data Structures And Algorithms

Inroduction to Data structures and Algorithms || Deepali Srivastava

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The book is available for download in "texts" format, the size of the file-s is: 96.86 Mbs, the file-s for this book were downloaded 74 times, the file-s went public at Tue Nov 05 2019.

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19Wiki - 6.006 Introduction To Algorithms

6.006 Introduction to Algorithms dumped with WikiTeam tools.

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The book is available for download in "web" format, the size of the file-s is: 0.43 Mbs, the file-s for this book were downloaded 118 times, the file-s went public at Sun Feb 09 2014.

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20Introduction To Engineering Programming : Solving Problems With Algorithms

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xx, 422 p. : 24 cm

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The book is available for download in "texts" format, the size of the file-s is: 964.06 Mbs, the file-s for this book were downloaded 119 times, the file-s went public at Mon May 30 2022.

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21Introduction To Algorithms : A Creative Approach

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xx, 422 p. : 24 cm

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22Introduction To Computer Science : Problems, Algorithms, Languages, Information And Computers

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Bibliography: p. 455-456

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23Introduction To Distributed Algorithms

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Bibliography: p. 455-456

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24Introduction To Mathematical Programming: Applications And Algorithms

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Bibliography: p. 455-456

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25Introduction To The Design And Analysis Of Algorithms

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Bibliography: p. 455-456

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26Introduction To The Design & Analysis Of Algorithms

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Bibliography: p. 455-456

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27Introduction To Quantum Computers And Quantum Algorithms

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This is a short introduction to Quantum Computing intended for physicists. The basic idea of a quantum computer is introduced. Then we concentrate on Shor's integer factoring algorithm.

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28Design And Analysis Of Randomized Algorithms : Introduction To Design Paradigms

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This is a short introduction to Quantum Computing intended for physicists. The basic idea of a quantum computer is introduced. Then we concentrate on Shor's integer factoring algorithm.

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29An Introduction To Distributed Algorithms

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An Introduction to Distributed Algorithms Barbosa C. Valmir The MIT Press, 1996 Preface Part 1 - Fundamentals Chapter 1 - Message-Passing Systems Chapter 2 - Intrinsic Constraints Chapter 3 - Models of Computation Chapter 4 - Basic Algorithms Chapter 5 - Basic Techniques Part 2 - Advances and Applications Chapter 6 - Stable Properties Chapter 7 - Graph Algorithms Chapter 8 - Resource Sharing Chapter 9 - Program Debugging Chapter 10 - Simulation Bibliography Author Index Subject Index List of Figures List of Listings This book presents an introduction to some of the main problems, techniques, and algorithms underlying the programming of distributed-memory systems, such as computer networks, networks of workstations, and multiprocessors. It is intended mainly as a textbook for advanced undergraduates or first-year graduate students in computer science and requires no specific background beyond some familiarity with basic graph theory, although prior exposure to the main issues in concurrent programming and computer networks may also be helpful. In addition, researchers and practitioners working on distributed computing will also find it useful as a general reference on some of the most important issues in the field.

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30An Introduction To The Analysis Of Algorithms

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An Introduction to Distributed Algorithms Barbosa C. Valmir The MIT Press, 1996 Preface Part 1 - Fundamentals Chapter 1 - Message-Passing Systems Chapter 2 - Intrinsic Constraints Chapter 3 - Models of Computation Chapter 4 - Basic Algorithms Chapter 5 - Basic Techniques Part 2 - Advances and Applications Chapter 6 - Stable Properties Chapter 7 - Graph Algorithms Chapter 8 - Resource Sharing Chapter 9 - Program Debugging Chapter 10 - Simulation Bibliography Author Index Subject Index List of Figures List of Listings This book presents an introduction to some of the main problems, techniques, and algorithms underlying the programming of distributed-memory systems, such as computer networks, networks of workstations, and multiprocessors. It is intended mainly as a textbook for advanced undergraduates or first-year graduate students in computer science and requires no specific background beyond some familiarity with basic graph theory, although prior exposure to the main issues in concurrent programming and computer networks may also be helpful. In addition, researchers and practitioners working on distributed computing will also find it useful as a general reference on some of the most important issues in the field.

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31Introduction To Algorithms - A Minicourse On Dynamic Multithreaded Algorithms

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Abstract: This tutorial teaches dynamic multithreaded algorithms using a Cilk-like [11, 8, 10] model. The material was taught in the MIT undergraduate class 6.046 Introduction to Algorithms as two 80-minute lectures. The style of the lecture notes follows that of the textbook by Cormen, Leiserson, Rivest, and Stein [7], but the pseudocode from that textbook has been �Cilki�ed� to allow it to describe multithreaded algorithms. The �rst lecture teaches the basics behind multithreading, including de�ning the measures of work and critical-path length. It culminates in the greedy scheduling theorem due to Graham and Brent [9, 6]. The second lecture shows how parallel applications, including matrix multiplication and sorting, can be analyzed using divide-and-conquer recurrences.

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32An Introduction To Genetic Algorithms

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Contents: An Introduction to Genetic Algorithms; Genetic Algorithms: An Overview; Genetic Algorithms in Problem Solving; Genetic Algorithms in Scientific Models; Theoretical Foundations of Genetic Algorithms; Conclusions and Future Directions. Lecture Notes Collection FreeScience.info ID2813 Obtained from http://www.boente.eti.br/fuzzy/ebook-fuzzy-mitchell.pdf http://www.freescience.info/go.php?pagename=books&id=2813

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33An Introduction To MM Algorithms For Machine Learning And Statistical

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MM (majorization--minimization) algorithms are an increasingly popular tool for solving optimization problems in machine learning and statistical estimation. This article introduces the MM algorithm framework in general and via three popular example applications: Gaussian mixture regressions, multinomial logistic regressions, and support vector machines. Specific algorithms for the three examples are derived and numerical demonstrations are presented. Theoretical and practical aspects of MM algorithm design are discussed.

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34Pascal And Algorithms : An Introduction To Problem Solving

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MM (majorization--minimization) algorithms are an increasingly popular tool for solving optimization problems in machine learning and statistical estimation. This article introduces the MM algorithm framework in general and via three popular example applications: Gaussian mixture regressions, multinomial logistic regressions, and support vector machines. Specific algorithms for the three examples are derived and numerical demonstrations are presented. Theoretical and practical aspects of MM algorithm design are discussed.

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35Introduction To Quantum Algorithms

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These notes discuss the quantum algorithms we know of that can solve problems significantly faster than the corresponding classical algorithms. So far, we have only discovered a few techniques which can produce speed up versus classical algorithms. It is not clear yet whether the reason for this is that we do not have enough intuition to discover more techniques, or that there are only a few problems for which quantum computers can significantly speed up the solution.

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36MIT 6.046J Introduction To Algorithms

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This course teaches techniques for the design and analysis of efficient algorithms, emphasizing methods useful in practice. Topics covered include: sorting; search trees, heaps, and hashing; divide-and-conquer; dynamic programming; amortized analysis; graph algorithms; shortest paths; network flow; computational geometry; number-theoretic algorithms; polynomial and matrix calculations; caching; and parallel computing.

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37Bisociative Knowledge Discovery: An Introduction To Concept, Algorithms, Tools, And Applications

Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Information Systems Applications (incl. Internet); User Interfaces and Human Computer Interaction; Pattern Recognition; Computer Communication Networks

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38MIT 3 Divide & Conquer: FFT - Design And Analysis Of Algorithms - Introduction To Alogorithms

MIT Design and Analysis of Algorithms Prof. Erik Demaine Prof. Srini Devadas Prof. Nancy Lynch MIT Course Number 6.046J / 18.410J As Taught In Spring 2015 Level Undergraduate

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39Introduction To Algorithms - Lecture Notes On Skip Lists

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MIT Design and Analysis of Algorithms Prof. Erik Demaine Prof. Srini Devadas Prof. Nancy Lynch MIT Course Number 6.046J / 18.410J As Taught In Spring 2015 Level Undergraduate

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40Introduction To The Design & Analysis Of Algorithms

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All IT background students can go through this book

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41Ideals, Varieties, And Algorithms : An Introduction To Computational Algebraic Geometry And Commutative Algebra

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XIII, 538 p

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42An Introduction To Bioinformatics Algorithms

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XIII, 538 p

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43Introduction To Computing And Algorithms

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XIII, 538 p

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44T4PG-WSVP: Coding The Law: An Introduction To Algorithms In …

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45An Introduction To Distributed Algorithms

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46MIT OCW 6.006 - Introduction To Algorithms, Fall 2011

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This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performance measures and analysis techniques for these problems.

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47Introduction To Algorithms A Creative Approach Udi Manber [ PASHA. BHAI]™

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48An Introduction To Genetic Algorithms For Scientists And Engineers

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49Ji Suan Ji Suan Fa : She Ji Yu Fen Xi Dao Lun (di 3 Ban, Ying Yin Ban) = Computer Algorithms : Introduction To Design And Analysis.(third Edition)

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50X 2 Download.app Introduction To Linked List Data Structures & Algorithms Java Placement Course ( 1080p)

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