|Sold by:|| Penguin Random House Publisher Services |
Price set by seller.
Your Memberships & Subscriptions
Introduction to Algorithms, third edition Kindle Edition
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.
"In light of the explosive growth in the amount of data and the diversity of computing applications, efficient algorithms are needed now more than ever. This beautifully written, thoughtfully organized book is the definitive introductory book on the design and analysis of algorithms. The first half offers an effective method to teach and study algorithms; the second half then engages more advanced readers and curious students with compelling material on both the possibilities and the challenges in this fascinating field."--Shang-Hua Teng, University of Southern California
""Introduction to Algorithms, " the 'bible' of the field, is a comprehensive textbook covering the full spectrum of modern algorithms: from the fastest algorithms and data structures to polynomial-time algorithms for seemingly intractable problems, from classical algorithms in graph theory to special algorithms for string matching, computational geometry, and number theory. The revised third edition notably adds a chapter on van Emde Boas trees, one of the most useful data structures, and on multithreaded algorithms, a topic of increasing importance."--Daniel Spielman, Department of Computer Science, Yale University
"As an educator and researcher in the field of algorithms for over two decades, I can unequivocally say that the Cormen book is the best textbook that I have ever seen on this subject. It offers an incisive, encyclopedic, and modern treatment of algorithms, and our department will continue to use it for teaching at both the graduate and undergraduate levels, as well as a reliable research reference."--Gabriel Robins, Department of Computer Science, University of Virginia --This text refers to an alternate kindle_edition edition.
About the Author
Charles E. Leiserson is Professor of Computer Science and Engineering at the Massachusetts Institute of Technology.
Ronald L. Rivest is Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology.
Clifford Stein is Professor of Industrial Engineering and Operations Research at Columbia University. --This text refers to an alternate kindle_edition edition.
- ASIN : B08FH8N996
- Publisher : The MIT Press (July 31, 2009)
- Publication date : July 31, 2009
- Language : English
- File size : 15688 KB
- Text-to-Speech : Enabled
- Screen Reader : Supported
- Enhanced typesetting : Enabled
- X-Ray : Not Enabled
- Word Wise : Not Enabled
- Print length : 2059 pages
- Lending : Not Enabled
- Best Sellers Rank: #182,624 in Kindle Store (See Top 100 in Kindle Store)
- Customer Reviews:
About the authors
Reviewed in the United States on September 25, 2021
Reviews with images
Top reviews from the United States
There was a problem filtering reviews right now. Please try again later.
I then re-read the section and take notes. I find that I feel somewhat lost at first when the book introduces a topic that I am unfamiliar with, but after reviewing it from a high level (youtube video) it helps me understand the algorithm on a surface level. Once I understand it in its simplest terms, the proofs become much simpler and they make a lot of sense.
I think to get everything out of this text you should be comfortable with data-structures, linear algebra and discrete mathematics. I found discrete math and linear algebra to be difficult courses, but this text is increasing my confidence in how much I had learned in those courses.
Great text but at times I feel lost. I wish the examples were more comprehensive at times.
- The introduction (Chapters 1-4) is really good and does a good job setting up all the fundamental concepts of algorithms. I think a lot of people tend to skip over introductions because they think they know all of it already, but this is an introduction that I recommend reading the whole way through.
- The book is a pretty light read (none of the math is too difficult) and each chapter is a good length.
- I think the material on dynamic programming and greedy algorithms was particularly enlightening, and if you read it the whole way through you actually learn how to prove that greedy algorithms work, instead of just being like "let's use a greedy algorithm because it seems right"
- I was able to copy a lot of CLRS code almost verbatim in my programming interviews and pass them.
- The figures are really well done and informative.
- The pseudocode has a lot of one-letter variable names, and while this follows the tradition of pure math, it also makes understanding the algorithms more difficult than it should be.
- Sometimes the pseudocode is not the "easiest" possible pseudocode (for example, merge sort), and I think it would be better if the authors presented a simpler version of the pseudocode first and then extended it to the optimal version. But then I guess CLRS would be even longer than it already is.
- The arrays are 1-indexed, which makes it trickier to convert to code. Also there are some sections of the textbook (the counting sort section) where some of the arrays are 0-indexed and other arrays are 1-indexed, which is just weird.
- I think the material on graphs, particularly the derivations, could be done in a more engaging and intuitive way. The derivations in Chapters 22-24 were a long series of small uninteresting lemmas, instead of a small number of harder, more insightful theorems. I found derivations elsewhere on the internet that were a lot more interesting and built more intuition about why the procedures worked. I feel like the rest of the book is pretty good though, so maybe all the graph stuff was written by a separate person who is not very good at explaining things.
This book is impressive! It covers a lot of subject matter and is clearly worded. However, you're going to get lost because this often reads more like a reference manual than a conversation that appeals to intuition. You'll be pushed into analyzing algorithms for theoretical data structures that you fuzzily remember (if at all). But, nonetheless, throw enough man hours into this book and you will learn concrete approaches to determining just how hard you're making the computer work.
My biggest criticism is that, as an *introduction*, this book doesn't do the best job at warming up readers to new tools and methodologies. This is an 'eh, just push them into the deep end' kind of approach to learning.
I got it to supplement my professor's original recommendation (for COS 485/585 at the University of Southern Maine), which was Namipour Kumarss's 'Foundations of Algorithms'. It definitely covered more of the class than the text, because we already had alternative sources in addition to 'Foundations'.
Get the PDF if possible, because it's faster to search it doesn't follow the same organization of your class.
If you can, get the solution manual as well - it's worth working out the problems in addition to your other homework.
To anyone studying algorithms, good luck! Don't forget there are also great video resources as well.
Top reviews from other countries
But I got it for a price of 900 Rs. Still, it's not correct for the seller to ship a Xerox copy. And the quality of the xerox is not good as well because in many pages, the ink is too light and almost not readable.
Coming to the book itself, it's a great book and no doubt it. Recommend this book to anyone who wants to study algorithms.
Reviewed in India on November 8, 2020
Reviewed in the United Kingdom on March 24, 2019
That said, the approach, whilst detailed, is at times quite dry and heavy going, and could perhaps be broken up a little more to keep the reader refreshed and focused.
On balance given 5* for comprehensive coverage of algorithms and clear descriptions - but don't expect a pure cookbook of algorithms that can be typed in or downloaded.