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Introduction To Algorithms (Hardcover) by Thomas H. Cormen, Charles E.

Introduction To Algorithms (Hardcover) by Thomas H. Cormen, Charles E.
Introduction To Algorithms (Hardcover) by Thomas H. Cormen, Charles E. Leiserson, etc.
Introduction To Algorithms (Hardcover) by Thomas H. Cormen, Charles E. Leiserson, etc.
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Introduction To Algorithms (Hardcover) by Thomas H. Cormen, Charles E. Leiserson, etc.

Introduction To Algorithms (Hardcover) by Thomas H. Cormen, Charles E. Leiserson, etc.

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  • Publisher: ‎ MIT Press; 4th edition

    Publication Date: April 5th, 2022

    Language: ‎ English

    Binding: Hardcover

    Pages: ‎ 1332

    ISBN-13: ‎ 9780262046305

    Item Weight ‏(gram): ‎ 2180

    Dimensions ‏(cm): ‎ 21.29 x 5.54 x 23.65

  • 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 learning
    • New material on topics including solving recurrence equations, hash tables, potential functions, and suffix arrays
    • 140 new exercises and 22 new problems
    • Reader feedback–informed improvements to old problems
    • Clearer, more personal, and gender-neutral writing style
    • Color added to improve visual presentation
    • Notes, bibliography, and index updated to reflect developments in the field
    • Website with new supplementary material

  • 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.

  • Publisher: ‎ MIT Press; 4th edition

    Publication Date: April 5th, 2022

    Language: ‎ English

    Binding: Hardcover

    Pages: ‎ 1332

    ISBN-13: ‎ 9780262046305

    Item Weight ‏(gram): ‎ 2180

    Dimensions ‏(cm): ‎ 21.29 x 5.54 x 23.65

  • 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 learning
    • New material on topics including solving recurrence equations, hash tables, potential functions, and suffix arrays
    • 140 new exercises and 22 new problems
    • Reader feedback–informed improvements to old problems
    • Clearer, more personal, and gender-neutral writing style
    • Color added to improve visual presentation
    • Notes, bibliography, and index updated to reflect developments in the field
    • Website with new supplementary material

  • 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.

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