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57 of 61 people found the following review helpful
5.0 out of 5 stars Detailed, clear and complete
The flow in this book is excellent. The authors do a great job in organizing this book in logical chapter. The chapters are organized into techniques to find solutions to particular problems, like for example, Greedy Algorithms, Divide and Conquer, and Dynamic Programming.

Each chapter contains a few representative problems of the technique or topic discussed...
Published on July 18, 2005 by Szymon Rozga

versus
26 of 31 people found the following review helpful
2.0 out of 5 stars Highly overrated
Broad coverage. Poor organization. I used to use it as a text book for a first course in algorithms, in the Open University of Israel while I was teaching there.
Absolutely inferior to Cormen for an introductory course on algorithms.
Hardly adequate for self study.
The authors structure the book according to an "algorithmic design strategy" concept - that...
Published on February 26, 2011 by Ariel Yaroshevich


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57 of 61 people found the following review helpful
5.0 out of 5 stars Detailed, clear and complete, July 18, 2005
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This review is from: Algorithm Design (Hardcover)
The flow in this book is excellent. The authors do a great job in organizing this book in logical chapter. The chapters are organized into techniques to find solutions to particular problems, like for example, Greedy Algorithms, Divide and Conquer, and Dynamic Programming.

Each chapter contains a few representative problems of the technique or topic discussed. These are discussed in great detail, which is helpful to initially grasp the concepts. Furthermore, the end of each chapter contains a number of solved exercises. These are written up in less detail than the chapter problems, because they are usually slight variations or applications of the representative problems. I found these to be very helpful to me, as to build up a stronger grasp of the problem at hand.

Furthemore, the progressive search for a solution, such as for the Weighted Interval Scheduling problem using dynamic programming, is essential to understanding the process through which we can find such algorithms. The book is well written, in a clear, understandable language. The supplementary chapters on Basics of Algorithm Analysis and Graph Theory are a great started for people who have not been exposed to those concepts previously.

Network flows are covered extensively with their applications. I suppose this section of the course was enhanced because our instructor's research interests are Network Flows and she threw example after example at us. There are a great number of problems at the end of this chapter to practice.

(...)
One of the strenghs of this book, is that when the authors determine the running time of a particular algorithm, they write about how to implement it, with which data structures and why. Although it is assumed that data structures are common knowledge for the reader, this type of analysis is helpful for further understanding of such structures.

All in all, this is a great textbook for an introductory course in the design of algorithms.
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33 of 34 people found the following review helpful
5.0 out of 5 stars Slightly better than Cormen - highly readable, June 11, 2007
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This review is from: Algorithm Design (Hardcover)
Best undergraduate handbook about algorithms i've seen so far.
Examples are much less artificial than in CLRS (Introduction to Algorithms). Most of them are highly practical, e.g. using Kruskal's MST algorithm as a simple clustering device.
It's worth mentioning that E.Tardos is a world-class calibre specialist in graph algorithms. When you feel unsatisfied with network flows chapter, you can read her survey of network flows (written with two other graph titans - Goldberg and Tarjan)
The division into chapters is good, yet classical. There are also exercises after each chapter, lots of them, good for preparation if you have algorithm-oriented job interview (Google, Yahoo, Microsoft etc.).

What's next? Read Tarjan's evergreen classic - Data Structures and Network Algorithms.
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36 of 41 people found the following review helpful
5.0 out of 5 stars dealing with NP completeness, July 30, 2005
This review is from: Algorithm Design (Hardcover)
The text offers an interesting blend of rigour and informality. The numerous proofs in each chapter have that rigour. Yet what may be more important is how the text remains accessible to a primarily undergraduate audience.

The book is not just a compendium of common algorithms in computer science, and proofs about them. The authors place a stronger emphasis on motivating how to develop an intuitive understanding of the problems that the algorithms address, and of how to shape new algorithms. Or, possibly, apply or modify existing algorithms to new problems.

If you compare the text to Knuth's classic "Art of Computer Programming", then you might find Kleinberg and Tardos more accessible. (At least for undergraduate readership.)

Also, the extensive exercises at the end of each chapter often have contexts germane to the Web. For example, the links in web pages are used to motivate problems in graph theory, where we have directed (unidirectional) graphs, due to the one way nature of links. More generally, the recent, contextual nature of the problems may appeal to some students. Knuth had many exercises listed in his books, but they can be too abstract for most students.

The text also has an interesting chapter on NP problems. The authors address a very practical situation. Even if you find that you have a problem that is NP complete, it is not necessarily the end of the story. For real life reasons, you may have to find an approximate solution that is computationally feasible to evaluate. The chapter offers suggestions and examples that may be of help. (More formal texts might merely stop at proving NP completeness.)
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26 of 31 people found the following review helpful
2.0 out of 5 stars Highly overrated, February 26, 2011
This review is from: Algorithm Design (Hardcover)
Broad coverage. Poor organization. I used to use it as a text book for a first course in algorithms, in the Open University of Israel while I was teaching there.
Absolutely inferior to Cormen for an introductory course on algorithms.
Hardly adequate for self study.
The authors structure the book according to an "algorithmic design strategy" concept - that is, Greedy, Divide and Conquer, Dynamic programming, etc... but but soon enough they're out of ideas, as the later chapters just follow the standard topics of any other text book: network flow, NP-completeness, approximation algorithms, heuristic search etc... (although, as said - the coverage is pretty broad).

The problem with such an approach, as much as it might be appealing for a mature computer scientist, is, that for a student, grasping the "paradigm" or an "algorithmic strategy" is almost impossible, especially when he learned about BFS, DFS and Dijkstra's algorithms about two weeks ago. It just makes him confused.

The authors try to develop the "right" algorithm in an incremental way, which may be an appropriate in a class room, but in a text book it is, once again, just confusing. You can never know if the current version of the algorithm is "the canonical one", or just another thought experiment. Even when the final version of the algorithm is presented - the pseudo code is excruciatingly terse, the complexity isn't clearly stated in the same paragraph, but mentioned in some remote part of the discussion.

Even the pseudo code typography looks like a Telnet printout from the 70s. How I missed the elegant notation of Cormen, not to mention Knuth...

In addition, the authors try to give "sexy" real world examples on every possible occasion: search engines, network routing, image processing - you name it. Once again, the baffled student, before he groked the basic flow of the algorithm, his is overwhelmed with irrelevant details.

If you already have at least Bsc in c.s. it'll give you some nice insights, and a cozy feeling, like you're having a pretentious small talk with the two rising stars of theoretical computer science. But for the freshmen - I'd recommend Cormen.
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12 of 13 people found the following review helpful
5.0 out of 5 stars Excellent book, but do NOT buy the Kindle edition!, December 10, 2011
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This review is from: Algorithm Design (Kindle Edition)
This review is for the Kindle edition of "Algorithm Design" by Kleinberg and Tardos Algorithm Design

This book is wonderfully organized. I used it for an Algorithms course and it's just very well laid out, with a nice progression of topics. If you want to gain a good "overall" picture of algorithms, this book is perfect. As with any kind of math, if you want to go much deeper, you'll need specialized textbooks for particular topics, but for a reasonably complete, holistic, one-semester course, you'll love this book. I should also point out that there are several well-crafted exercises in each chapter to cement your understanding and give your grey matter a good workout!

IMPORTANT: The Kindle edition of this book is a horribly travesty to the non-digital edition. The typesetting is crude (Amazon, you can do way better!), important figures/diagrams are scaled to tiny sizes, and formulas just plain look incorrect. My best guess is that this was re-typeset by hand, by a non-technical person using MS Word, so they simply messed it up badly. Personally, I am kicking myself for having paid nearly $90 for this, when I could've bought the "real" textbook for $110.

I was sorely tempted to give it a one-star review, but the content is top-notch, brilliantly put-together and an asset to any student of Computer Science. To recap: DO NOT BUY THE KINDLE EDITION!

If you do buy the Kindle edition after reading this review, you'll only have yourself to blame.
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16 of 19 people found the following review helpful
3.0 out of 5 stars One of the better introduction algorithm books, December 10, 2006
This review is from: Algorithm Design (Hardcover)
With algorithms not a strength of mine (although I am a computer scientist student), I was quite happy that our professor switched to this book away from the MIT Press book. The first few chapters were exactly what I needed in order to finally get a grasp of key algorithm analysis and design concepts. As the book progressed to more difficult chapters, their explanations became less and less clear and seemed to rely more on text than on nice diagrams and graphics. A few complaints I have about the book: no mention of the Master Method in the dynamic programming chapter, NP-Complete explanation confusing, and no published errata that I could find. Although I have a few complaints about the book, it is one of the better books for being introduced to algorithms. It needs a little tuning now and then as some explanations are not so clear, but you'll find even more complicated explinations in other algorithm books.
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8 of 9 people found the following review helpful
4.0 out of 5 stars Interesting Problem Sets, November 4, 2007
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Craig (San Diego, CA, United States) - See all my reviews
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This review is from: Algorithm Design (Hardcover)
I think the book Algorithms (Sanjoy Dasgupta, Christos H. Papadimitriou, and Umesh Vazirani), is better written and more succint but nonetheless Algorithm Design is an excellent book. Its problems sets are very interesting (often posed from real world perspectives) and towards the end the depth of the material exceeds the much shorter Algorhithms book. You should probably get both.
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3 of 3 people found the following review helpful
2.0 out of 5 stars "Pretty much" doesn't cover anything fully, May 7, 2013
This review is from: Algorithm Design (Hardcover)
This book covers the entire array of topics one could hope to cover with any algorithms book, but the explanations and execution of proofs is severely lacking. The following are quotes from the book...

"This is pretty much all we need for the analysis" - Pg 731 on Finding Median

A fact/lemma 13.20 is presented as "The number of type j subproblems created by the algorithm is at most (4/3)^(j+1)". The following explanation starts off with "There are at most (4/3)^(j+1) subproblems of type j, and the expected time spent on each is ...".

Assumptions with no explanations plague this book, and often a proofs are lazily written as 'obviously we designed the algorithm to work, therefore it works'.

I am about to finish my Algorithms and Complexity class here at school, and I love the course and the content and plan on buying Algorithms (4th Edition) by Robert Sedgewick or The Algorithm Design Manual by Steve Skiena after the class ends as I value the content.

I could never recommend this book to anyone.
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3 of 3 people found the following review helpful
5.0 out of 5 stars I love it!, September 10, 2010
By 
Samir Bajaj (Seattle, WA USA) - See all my reviews
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This review is from: Algorithm Design (Hardcover)
This book reminds me of everything I love about algorithms. It is well-written, with just the right amount of mathematical rigor.

If you're looking for a "crash course" on algorithms because you have an interview next week, keep looking--this one is not for you.

I wish I had the authors as my teachers when I was in college.
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3 of 3 people found the following review helpful
4.0 out of 5 stars Succinctly presented, March 18, 2008
This review is from: Algorithm Design (Hardcover)
One of the better algorithm books I have studied. The content is succinctly presented. It does a good job at handling some complex topics. I like the way the book focuses on techniques for designing algorithms. Manages to bring forth important concepts in algorithm design while keeping the book to a manageable size.
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Algorithm Design
Algorithm Design by Jon Kleinberg (Hardcover - March 26, 2005)
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