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Algorithm Design: International Edition (Anglais) Broché – 1 juin 2005

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Broché, 1 juin 2005
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Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.

August 6, 2009 Author, Jon Kleinberg, was recently cited in the New York Times for his statistical analysis research in the Internet age.

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Couverture | Copyright | Table des matières | Extrait | Index | Quatrième de couverture
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58 internautes sur 62 ont trouvé ce commentaire utile 
Detailed, clear and complete 18 juillet 2005
Par Szymon Rozga - Publié sur Amazon.com
Format: Relié
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.
33 internautes sur 34 ont trouvé ce commentaire utile 
Slightly better than Cormen - highly readable 11 juin 2007
Par Przemyslaw Drochomirecki - Publié sur Amazon.com
Format: Relié Achat vérifié
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.
36 internautes sur 41 ont trouvé ce commentaire utile 
dealing with NP completeness 30 juillet 2005
Par W Boudville - Publié sur Amazon.com
Format: Relié
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.)
18 internautes sur 19 ont trouvé ce commentaire utile 
Excellent book, but do NOT buy the Kindle edition! 11 décembre 2011
Par Rahul Banerjee - Publié sur Amazon.com
Format: Format Kindle Achat vérifié
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.
28 internautes sur 34 ont trouvé ce commentaire utile 
Highly overrated 27 février 2011
Par Ariel Yaroshevich - Publié sur Amazon.com
Format: Relié
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 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. One can never know if the current version of the algorithm being presented is "the canonical one", or just another thought experiment. Even when the final version of the algorithm is finally there - the pseudo code is excruciatingly terse, the complexity isn't clearly stated in the same paragraph, and if you're lucky it will be mentioned in some remote part of the discussion.

Even the pseudo code typography looks like a Telnet printout from the 70s.
How much 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, the book makes him overwhelmed with tons of 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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