Introduction to Algorithms, Fourth Edition - by Thomas H Cormen & Charles E Leiserson & Ronald L Rivest & Clifford Stein (Hardcover)

About the Book

"The leading introductory textbook and reference on algorithms"--

Book Synopsis

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 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

Warning: Avoid counterfeit copies of Introduction to Algorithms by buying only from reputable retailers. Counterfeit and pirated copies are incomplete and contain errors.

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.