Introduction to Algorithms, fourth edition
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Description
A comprehensive update of the leading algorithms text, with new material on matchings in bipartite graphs, online algorithms, machine learning, and other topics.Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. It covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers, with self-contained chapters and algorithms in pseudocode. Since the publication of the first edition, Introduction to Algorithms has become the leading algorithms text in universities worldwide as well as the standard reference for professionals. This fourth edition has been updated throughout.New for the fourth edition New chapters on matchings in bipartite graphs, online algorithms, and machine learningNew material on topics including solving recurrence equations, hash tables, potential functions, and suffix arrays140 new exercises and 22 new problemsReader feedback–informed improvements to old problemsClearer, more personal, and gender-neutral writing styleColor added to improve visual presentationNotes, bibliography, and index updated to reflect developments in the fieldWebsite with new supplementary materialWarning: Avoid counterfeit copies of Introduction to Algorithms by buying only from reputable retailers. Counterfeit and pirated copies are incomplete and contain errors.
Additional information
Weight | 2.66 kg |
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Dimensions | 5.54 × 21.29 × 23.65 cm |
PubliCanadation City/Country | USA |
by | Charles E. Leiserson, Clifford Stein, Ronald L. Rivest, Thomas H. Cormen |
Format | Hardback |
Language | |
Pages | 1312 |
Publisher | |
Year Published | 2022-4-5 |
Imprint | |
ISBN 10 | 026204630X |
About The Author | Thomas H. Cormen is Emeritus Professor of Computer Science at Dartmouth College. Charles E. Leiserson is Edwin Sibley Webster Professor in Electrical Engineering and Computer Science at MIT. Ronald L. Rivest is Institute Professor at MIT. Clifford Stein is Wai T. Chang Professor of Industrial Engineering and Operations Research, and of Computer Science at Columbia University. |
Table Of Content | Preface xiiiI FoundationsIntroduction 31 The Role of Algorithms in Computing 52 Getting Started 173 Characterizing Running Times 494 Divide-and-Conquer 765 Probabilistic Analysis and Randomized Algorithms 126II Sorting and Order Statistics Introduction 1576 Heapsort 1617 Quicksort 1828 Sorting in Linear Time 2059 Medians and Order Statistics 227III Data Structures Introduction 24910 Elementary Data Structures 25211 Hash Tables 27212 Binary Search Trees 31212 Red-Black Trees 331IV Advanced Design and Analysis Techniques Introduction 36114 Dynamic Programming 36215 Greedy Algorithms 41716 Amortized Analysis 448V Advanced Data StructuresIntroduction 47717 Augmenting Data Structures 48018 B-Trees 49719 Data Structures for Disjoint Sets 520VI Graph Algorithms Introduction 54720 Elementary Graph Algorithms 54921 Minimum Spanning Trees 58522 Single-Source Shortest Paths 60423 All-Pairs Shortest Paths 64624 Maximum Flow 67025 Matchings in Bipartite Graphs 704VII Selected TopicsIntroduction 74526 Parallel Algorithms 74827 Online Algorithms 79128 Matrix Operations 81929 Linear Programming 85030 Polynomials and the FFT 87731 Number-Theoretic Algorithms 90332 String Matching 95733 Machine-Learning Algorithms 100334 NP-Completeness 104235 Approximation Algorithms 1104VIII Appendix: Mathematical BackgroundIntroduction 1139A Summations 1140B Sets, Etc. 1153C Counting and Probability 1178D Matrices 1214Bibliography 1227Index 1251 |
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