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Introduction to Algorithms (Eastern Economy Edition)
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Review
"As an educator and researcher in the field of algorithms for over two decades, I can unequivocally say that the Cormen et al 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, Deptt. of Computer Science, University of Virginia "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, Deptt. of Computer Science, Yale University "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
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About the Author
Thomas H. Cormen received bachelor’s degree in Electrical Engineering from the Princeton University way back in 1978. Thereafter, he did his master’s in Electrical Engineering and Computer Science from the MIT. Among the students, he is best known for having co-authored a book titled 'Introduction to Algorithms'. In the year 2013, he published another book titled 'Algorithms Unlocked'. This book too has been received well. Charles E. Leiserson is Professor of Computer Science and Engineering at MIT. Ronald L. Rivest is Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT. Clifford Stein is Professor of Industrial Engineering and Operations Research at Columbia University.
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Product details
Paperback: 1312 pages
Publisher: PHI Learning Pvt. Ltd. (Originally MIT Press); Third edition (February 2, 2010)
Language: English
ISBN-10: 9788120340077
ISBN-13: 978-8120340077
ASIN: 8120340078
Product Dimensions:
11 x 8.5 x 1.2 inches
Shipping Weight: 3.7 pounds
Average Customer Review:
4.3 out of 5 stars
601 customer reviews
Amazon Best Sellers Rank:
#61,163 in Books (See Top 100 in Books)
An impressive volume that covers many many algorithmic strategies and is surely a major achievement in completeness and accuracy, and should also be pretty unique in its range from mathematical representations to concrete pseudo-code for algorithm implementation. Certainly a book to admire, featuring some excellent buildups and explanation paths. I imagine it to be highly esteemed as reference for undergraduate year-long series of lectures on algorithms in a university setting.As such it probably earns more than the 3 stars I will give it from my own perspective. My reasons for this are inherent in my own relationship to the topic - as a "user" if you will.I bought this book in order to dig deeper into my own conceptual understanding of algorithms, working by my myself.For this purpose I found the book to be quite tedious. Disadvantageous are especially the fetishization of compact representations, a tendency mathematicians are known to have.It really doesn't pull a lot of punches when it comes to dishing out mathematical expressions for the reader to patiently unfold for themselves in order to really grasp the meaning of the surrounding text - Ingestion of the material can become a true test of perseverance this way.It also needs to be said that this is one of these books that bears "Introduction" in the title when it works in fact more like an encyclopedic heavyweight 1200 page quasi-complete survey of the field.I'm writing this so you know what you are getting into. Be sure this is what you're looking for and what you need.
For background, I am a not-so-sharp CS undergrad that used this book for an intro. to algorithms class. I've done linear algebra, struggled my way through a "calculus" probability course, and enjoyed implementing many typical data structures. My learning style relies on simple examples (especially visual) accompanied by a concise explanation. Here are my thoughts: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 think this is a pretty good book that is easy to read if you have a strong background in proof-based math.Highlights:- 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.Drawbacks:- 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.
I'm reviewing this for what it is: An academic text that also serves as a collective document of algorithms for the community (computer science, etc.). This is not a beginner text. It's a first-class algorithms book that is very academically rigorous. That's not a put-down.Great reference and great read when you need to get out of the box and think creatively.For a more approachable intro to algorithms, check out Sedgewick's book. That book also has a companion website and Coursera course. it's hard to go wrong with that combo.
This is probably the most well known and most used textbook on the subject, and with good reason. An excellent resource, covering just about everything you need to know for a good understanding of Algorithms. (side tip, my friends in the industry call this the "How To Pass a Google Interview" book).My only complaint is that the binding has completely stated disintegrating after only 9 weeks of use. All of chapters 15 and 16 are completely falling out of my copy (and this is getting worse). Very disappointing as I plan on using it for a long time.
The printing is not clear.
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