Probability and Computing: Randomized Algorithms and Probabilistic Analysis

Book Description

Assuming only an elementary background in discrete mathematics, this textbook is an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. It includes random sampling, expectations, Markov's and Chevyshev's inequalities, Chernoff bounds, balls and bins models, the probabilistic method, Markov chains, MCMC, martingales, entropy, and other topics. The book is designed to accompany a one- or two-semester course for graduate students in computer science and applied mathematics.

Customer Reviews:

Advanced probability topics without measure theory.......2007-08-18

This book is underestimated by two reviewers below. I totally do not agree with them. This book covers a wide range of topics in a very readable style. The contents in this book is complementary to the book of Motwani and Raghavan (but this book is much easier to digest).

It, without requiring any knowledge on measure theory, contains excellent introductions to many difficult topics in probability including

- concentration bounds (Chernoff, Azuma-Hoeffding, etc.)
- applications of stochastic processes such as queuing theory
- martingale (Wald's equation)
- coupling of Markov chains and their mixing times
- Shannon's source coding and noisy channel theorems
- Erdos' probabilistic method
- etc.

All of these topics are provided with excellent applications in computing.
The authors illustrate many clever tricks for proving theorems, and these tricks give insights to the readers as well.

Just unnecessary.......2007-05-17

This book, while written by two renowned computer scientists, is truly disappointing. In trying to discuss randomness and computation, this book just does a mediocre job on discussing randomized computation and also an equally poor job discussing relevant aspects of probability theory. Their approach is not novel and many of their examples can be found in other texts. If you really want to learn randomized computation, get Motwani et al's book on Randomized Algorithms. If you want to learn probability theory, get any advanced probability theory book like Spencer and Alon on the probabilistic method, one of Sheldon Ross's books, or even Grimmett and Stirzaker. Whatever you do don't get this weak hybrid of a book that will require you to get another book at some point to supplement your understanding.

Another poorly written text book.......2006-03-19

The authors must be smart guys. They obviously understand alot about this subject but make the mistake that you do too! As a result, the book is inadequate as a teaching tool.

They use only half to a third of the narrative they need to adequately explain a subject. They also like to leave out proof steps or not explain them. The problems at the end of chapters are poor as well, since the authors seem to have forgotten to teach the techniques needed to solve most them in the chapter they belong to.

I am sure to them it is intuitive.

Good Introductory Textbook.......2005-03-16

It's pretty easy to get computers to do things where the answer is yes or no, or 4 or 6, given that the inputs to the problem are known. It's much harder to get an answer to a problem where the answer is that their is a 62% chance that the answer is yes. Unfortunately, in real life it's this second class of problems that predominates.

This book is oriented to solving these kinds of real world problems. The exercises in the book are chosen from real world examples -- what we used to call story problems. This tends to give the student a better understanding of not only the mathematics and programming involved but experience in looking at problems with a view to understanding this approach to solving the problem.

This book is suitable for a one or two semester introductory class at the upper undergraduate or beginning graduate level.

Just a word about the illustration on the front of the book. At the end of the book Alice in Wonderland the queen is about to order Alice beheaded. Alice says, "You're nothing but a pack of cards." At this, the whole pack rose up into the air and came flying down around her. This illustration is by John Tenniel from the original book of 1899. A deck of flying playing cards is a good way to illustrate random and probability.

Average customer rating:

very nice conceptual overview
Not for the practitioner
Trash
Excellent Introduction, Sparse on Details
A Good Introductory Survey

Scientific Computing
Michael T. Heath
Manufacturer: The McGraw-Hill Companies, Inc.
ProductGroup: Book
Binding: Hardcover

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ASIN: 0072399104

Book Description

Heath 2/e, presents a broad overview of numerical methods for solving all the major problems in scientific computing, including linear and nonlinear equations, least squares, eigenvalues, optimization, interpolation, integration, ordinary and partial differential equations, fast Fourier transforms, and random number generators. The treatment is comprehensive yet concise, software-oriented yet compatible with a variety of software packages and programming languages. The book features more than 160 examples, 500 review questions, 240 exercises, and 200 computer problems. Changes for the second edition include: expanded motivational discussions and examples; formal statements of all major algorithms; expanded discussions of existence, uniqueness, and conditioning for each type of problem so that students can recognize "good" and "bad" problem formulations and understand the corresponding quality of results produced; and expanded coverage of several topics, particularly eigenvalues and constrained optimization. The book contains a wealth of material and can be used in a variety of one- or two-term courses in computer science, mathematics, or engineering. Its comprehensiveness and modern perspective, as well as the software pointers provided, also make it a highly useful reference for practicing professionals who need to solve computational problems.

Customer Reviews:

very nice conceptual overview.......2006-07-22

Wow, people seem to be really split on this book. I had Mike Heath for numerical analysis/scientific computing and he was an excellent instructor, one of the best lecturers I've ever had. (As a consequence, I have a hard time separating the book and the class, so judge accordingly.) The book is based on his lecture notes, though he added some material and didn't cover every topic in the book. Just reading the book is useful to give you an overview of the point behind different methods. The goal of the class for which this book was written is actually quite conceptual. It was to give scientists (that's me: a stats researcher who makes heavy use of numerical computation) and CS people in areas other than scientific computing a leg up. It was only a first class for people in scientific computing, the rough equivalent of intro Physics or intro Probability/Stats for people in those respective majors. However, you *won't* be prepared to "roll your own" from this book. In fact, at the beginning of the semester Heath was very careful to note that if you have the opportunity to use a library function for most numerical programming, you are nuts to roll your own. Why? Numerical algorithms are usually extremely complicated and the authors of the code often spend years developing careful expertise on them. Frequently the formulas used to elucidate a given method are NOT the ones used to implement it. You need error traps, tricks to handle ill-scaling and other special cases, etc. These are things that someone who has a one-semester, superficial understanding of a topic simply won't have. So consider the book on the goals it set: it is an overview of a field. If you want to learn more about any one topic, you have to dig deeper and consult references and other works, but this is a good place to start. For this, the book serves admirably.

Not for the practitioner.......2005-11-17

If you are interested in Scientific computing from the viewpoint of the end user that is the guy who uses the method to solve practical engineering problems then this book is lacking.

Not enough methods in this book to constitute an introductory survey of the field. Every chapter gets heavy dose mathematical treatment, apparently Heath loves his math but for the rest of us it doesnt translate into know-how. Know how to solve equations using computational techniques. Very few derivations to back his mathematical swagger, very few examples (if any) and fewer numerical schemes to solve problems. Many of the chapters receive cursory treatment such as PDE's get about 70 pages of print. Far too little to do anyone any good.

He does talk about interesting issues such as conditioning and error analysis and computer precision and memory issues but it is done from such a superficial viewpoint that one cannot use anything to improve ones code. Not recommended if you want to learn numerical methods even if you have an excellent professor to learn from. His chapter on FFT's was even more abstruse and there was hardly any methods with which to solve PDE's.

I had this for a graduate course in Numerical Methods but ended up using Hoffman's excellent book on Numerical Methods.

Trash.......2005-10-14

If you want to have a solid understanding of numerical computation, this book is definitely the last choice. Many theorems are given without any proof or even intuitions behind them in this book. Even when a proof is provided, it's often far from rigorous. The organization of chapters is the worst I have ever seen, revelant materials are scattered over several different locations rather than put together. Take the SVD for example, it is mentioned in the end of chapter 3, but reappears in chapter 4, which is very confusing. If you are new to this area, please don't read this book. It gives you many many facts without explanations, which I think is not a good way to learn new things. David S. Watkins' Fundamentals of Matrix Computations is a lot better and easier to understand. It also emcompasses many detailed treatments of various theorems. If you have bought Heath's book, don't be sad, at least it can serve as a coaster.

Excellent Introduction, Sparse on Details.......2004-11-20

While sparse on the details of many of the algorithms and theorems mentioned, as an introduction it covers a broad range of material-enough for two semesters of study. The writing is lucid, and when a proof of a theorem is given, it is easy to follow and explained in english afterward. Rationale is given for everything, which is a great benefit to a student not familiar with the nuances of sophisticated linear algebra.

A Good Introductory Survey.......2002-11-05

This book excels at presenting a reader with little to no knowledge in computer science and a mild mathematical background (knowledge of differential equations as a prerequisite) with the fundamental concepts regarding scientific computing. The presentation of pseudo-code algorithms helps smooth the transition from analytical (pencil and paper) thinking to numerical thinking. The algorithms are presented in a manner such tha anyone with access to dozens of possible environments can apply them, though they are by no means complete, thus requiring some thought into the processes. The material covered is 110% of what an engineer will want to know, 90% of what an applied mathematician will want to know, and 45% of what a numerical analyist will want to know. In all, a great book to begin a foray into numerical computing.

A Wavelet Tour of Signal Processing, Second Edition (Wavelet Analysis & Its Applications)

Average customer rating:

Great Book
The most universal treatment of the subject
The worst textbook I have ever seen
Algorithms and much more!
A bold approach to wavelet transforms that simplifies

A Wavelet Tour of Signal Processing, Second Edition (Wavelet Analysis & Its Applications)
Stéphane Mallat
Manufacturer: Academic Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 012466606X

Book Description

This book is intended to serve as an invaluable reference for anyone concerned with the application of wavelets to signal processing. It has evolved from material used to teach "wavelet signal processing" courses in electrical engineering departments at Massachusetts Institute of Technology and Tel Aviv University, as well as applied mathematics departments at the Courant Institute of New York University and École
Polytechnique in Paris.

Key Features
* Provides a broad perspective on the principles and applications of transient signal processing with wavelets
* Emphasizes intuitive understanding, while providing the mathematical foundations and description of fast algorithms
* Numerous examples of real applications to noise removal, deconvolution, audio and image compression, singularity and edge detection,
multifractal analysis, and time-varying frequency measurements
* Algorithms and numerical examples are implemented in Wavelab, which is a Matlab toolbox freely available over the Internet
* Content is accessible on several level of complexity, depending on the individual reader's needs
New to the Second Edition
* Optical flow calculation and video compression algorithms
* Image models with bounded variation functions
* Bayes and Minimax theories for signal estimation
* 200 pages rewritten and most illustrations redrawn
* More problems and topics for a graduate course in wavelet signal processing, in engineering and applied mathematics

Customer Reviews:

Great Book.......2007-03-20

A great tool for Harmonic Analysis. The book is really well written, a most read for any one who is interested in the area of wavelets, S.P. or harmonic analysis.

The most universal treatment of the subject.......2005-06-08

I say universal because this book would appeal to engineers, computer scientists, and mathematicians alike. Mallat was particularly successful to present the topic in a sufficiently rigorous way but without losing sight of the practical and more intuitive side. The presentation comprises the mathematical and the signal processing viewpoints simultaneously. The wavelet field is very vast by now with several subfields. In this respect, Mallat made a great selection of topics in this book. There is a chapter on estimation which offers great review material and pretty much the state-of-the art on signal estimation over a wavelet basis. The chapter on approximation is particularly useful for those who are not well versed in approximation theory and thus are unable to understand other treatments. If you're interested in learning wavelet theory to solve practical problems such as image compression, signal estimation, etc, this is the book to have.

The worst textbook I have ever seen.......2004-02-12

I just finished Chapter 3 of this book, but I have had enough of it. Conceptions about Fourier Transform are not clear at all. And the most unbearable thing is that, there are many printing errors which may lead to misunderstanding.

Algorithms and much more!.......2002-07-10

The subject of wavelets has many facets, --infinite in all directions;-- some of the more exciting sides of the subject
are algorithmic, and the underlying mathematical principles are both simple and powerful. Stephane Mallat's great, and readable, book, in both of its editions, brings
this out wonderfully!

A bold approach to wavelet transforms that simplifies.......2002-04-24

This is an outstanding tour through the field of wavelet decompositions of both continuous and discrete signals. It employs the formalism of Hilbert space, instead of linear algebra. This is important because the power of this formalism yields insights into the subject matter that are practically impossible in linear algebra. The formalized approach allows a wide variety of subjects to be placed on a common basis (no pun intended). For example, the transition of the treatment of the Fourier transform into Hilbert space, brings to bear the powerful guns of that space (such guns as inner product and completeness), and allows for a truly elegant proof of the Parseval and Plancherel formulas.
Parseval's theorem, simply stated, is that the inner products in Hilbert space are conserved by the Fourier transform. How simple. Linear algebra approaches cannot hope to make things this simple.

Proof of the General Sampling Theorem is equally elegant; it is shown that the projection of the function to be decomposed onto a basis function gives the discrete spectral coefficient.

Readers will also enjoy the treatment of windowed Fourier transforms and frames.

I should add a note about the style of the treatise. This treatise is not ordinary. It consistently uses very precise and carefully defined symbology. Contrary to popular belief, this makes the text easier to read, not more difficult. Once the reader understands the symbol set being used (they are all defined in the front of the text), even the proofs are tractable. Yes, I said proofs. That is another aspect of the text. There are proofs embedded in the text, without loss of continuity or clarity. Proofs are necessary to a good understanding of the subject matter. The formalism of theorems, lemmas and propositions makes the conclusions understandable, because the theorems, lemmas and propositions supporting the conclusions are identifiable.

I applaud the author for his approach and recommend that other text book writers use the same approach.

Average customer rating:

This is a fantastic book!
Absolute essential
Fun, interesting and useful
A rich resource for low-level arithmetic tricks
Super Book

Hacker's Delight
Henry S. Warren Jr.
Manufacturer: Addison-Wesley Professional
ProductGroup: Book
Binding: Hardcover

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ASIN: 0201914654

Customer Reviews:

This is a fantastic book!.......2007-03-24

I have a virtual calculator called the DIY Calculator that accompanies my own book "How Computers Do Math" The Definitive Guide to How Computers Do Math : Featuring the Virtual DIY Calculator.

I recently added a "Conundrums, Puzzles, and Posers" section to the "Programs and Subroutines" page on my DIY Calculator website ([...]) and I've started to build a collection of simple puzzles for people to play with.

One of the first problems I posed was to count the number of ones in the 8-bit accumulator and to present the result as a binary value. I thought I had discovered the best-possible solution, until someone pointed me in the direction of the "Hacker's Delight". (In this context, "Hacker" refers to a hero who is manipulating code; not a nefarious rapscallion who breaks into other people's computer systems.)

I immediately ordered a copy from Amazon, and took delivery just yesterday as I pen these words. This book is fantastic - I kid you not - on the first page of Chapter 2, for example, I discovered at least five or six capriciously clever tricks that blew my solutions out of the water!

I highly recommend this book.

Absolute essential.......2007-02-28

This book is an absolute essential to the right reader. That right reader is either a low-level coder, a high-level logic designer, or someone who builds tools and libraries for same. In other words, not a lot of people. This is hacking at its bit-level finest, though. If you're among those few, or think you might be, or want a good laugh at the people who are, dig in.

It's good for things like counting the number of 1 bits in a word-length integer (hint: if you count the bits, you're doing it the hard way). It's good for things like fast division by an integer constant, or mod to a constant integer modulus (hint: if you perform division by dividing, you're barking up the wrong tree). If you can look into a 32x32 bit multiplication and see a convolution going on, you're way ahead of the game. The only tricks I know that didn't appear here are A) for purposes that almost no one has or B) for machines that almost no one has.

Warren presents the coolest collection of slimy coding tricks ever collected, with full attention to the number of machine cycles and the compiler-writer's unique needs. I've seen a lot, and this is by far the biggest and coolest collection around. I have two complaints, though, a small one and a really big one. The small one is that the author didn't score a direct bullseye on my somewhat offbeat needs. Well, he never tried to - that's just me griping that he didn't write a different book. The big complaint is that pages, lots of them, just fluttered out of this pricey book and onto the floor. GRRR. This takes nothing away from the content of the book, until some critical page flutters off never to be seen again. Still, if you can keep a rubber band around it, this will be one of the deepest mines of coolness in your uber-geek library.

//wiredweird

Fun, interesting and useful.......2007-01-24

My first introduction to binary operators wizardry was in a 1st year, 1st semester course in Digital Systems at the Technion, IIT. I thought it was fun. While I was trying to write a computer program to compute Karnaugh Maps for me, I run into performance problems, and then some binary hackery helped me get back on the horse.

Since then, whenever I come across some binary trick I write it down with a few examples of usage and sometimes with some reasoning why it works.

Then came "Hacker's Delight" and I felt compelled to buy it.

I wasn't disappointed at all! Not only it contained all of the tricks that I have collected, but also it contains a lot more in depth examples of how these tricks can come in handy when trying to squeeze performance from an implementation or save a few more bytes and bits.

The book also gave me a fresh perspective on the implementation of some well known algorithms with the twist of binary arithmetic. This was very enlightening.

I read the "BASICS" chapter (chapter 2) with a single breath of air, and just couldn't leave it down. Not only it was nice to have all these tricks summarized in one book, but also I liked some of the reasoning and the "so-called" proofs.

Remaining chapters were, as I mentioned before, a fresh look for me on known algorithms. This fresh look was through the glasses of binary arithmetic.

I'd recommend this book to anyone who feels comfortable with binary arithmetic and/or computer organization -- even just for the fun of it!

I'd recommend the book to developers who don't necessarily have a sympathy to this topic, but would like a Copy&Paste solution to some problems they have to tackle.

I really enjoyed reading this book, and I will probably reference it from time to time.

A rich resource for low-level arithmetic tricks.......2007-01-24

The term "hacker" in this book means someone who enjoys making computers do interesting tricks regardless of whether it turns out to be useful, not someone who is intent on circumventing computer security. Plus, how relevant would those kind of tips be coming from a book that was written in 2002? Don't let the author's definition of a hacker fool you, though - the tricks in this book are very useful.

This book is a collection of small programming tricks on various subjects. The presentation is very informal, and the methods use very basic computer math. You should know your binary number system backwards and forwards before you start this book. Either C or assembly language is used to demonstrate the hacks in code form. When assembly language is used, it is that of a fictitious machine that is representative of RISC computers. That is because the tricks are meant to be platform independent.

After disposing of basic arithmetic operations early in the book, the author turns his attention to more complex math problems such as calculating square roots. His discussion of the subject is both complex and simple. First, he explains Newton's method of computing square roots through a page full of equations that require some effort to follow. Then he gives an implementation that requires fewer than twenty lines of C code. This is followed by another method that is longer and more cryptic but executes faster, by using a binary search algorithm. Whether you are interested in the equations or merely need the C code to do your job, these solutions are efficient and elegant.

Other topics addressed include Gray codes, the Hilbert curve, and prime numbers. Gray codes are a method of arranging the integers from 1 to N in a list so that each number can be visited exactly once by flipping only one bit at a time. The Hilbert curve is a similar idea expressed geometrically: a single continuous curve which, given a space divided into a grid of squares, touches every square exactly once and does not cross itself. In each case, both the mathematical discussion and the code to solve the problem are provided.

The chapter on prime numbers is the most challenging mathematically but also one of the most interesting. It starts with a concise overview of various mathematicians' efforts to devise ways of finding prime numbers. The author is one of those people who periodically become fascinated by some problem and devote themselves to learning more about it and searching for a solution. The chapter ends not with the usual code sample, but instead with an invitation to continue the search for interesting solutions to the problem.

Clearly, the author views this book not as a finished collection, but rather as a snapshot of work in progress. After decades of interest-driven research, the author has amassed a collection of studies big enough to fill a book, and it is fortunate for the rest of us that he has written one.

Super Book.......2005-08-15

They don't make them like this anymore. Amid the "Learning XXX in 21 days" and various other computer book for which depth is almost non existent (and are read like eating peanuts), this is a refreshing book that talks about solutions to sometimes common (IMHO) coding problems.
If you enjoy programming gems, or remember that beyond your C code there is a machine that executes your program, this is the book for you. For example, think how would you count the 1 bits in a 32 bit integer - the book has an elegant solution in log(n). Aside from this, the book has about 50 or so problems, with their solutions (and proof).
Bottom line: fine book, worthy to be near my Knoth, R&K and Stroustrup books.

Network Flows: Theory, Algorithms, and Applications

Average customer rating:

the best network flow book for computer scientists
Good Introductory Book
Great book for Network Theory and Application
Great book for Network Theory and Application
PLEASE, write a corrected edition!

Network Flows: Theory, Algorithms, and Applications
Ravindra K. Ahuja , Thomas L. Magnanti , and James B. Orlin
Manufacturer: Prentice Hall
ProductGroup: Book
Binding: Hardcover

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ASIN: 013617549X

Book Description

Bringing together the classic and the contemporary aspects of the field, this comprehensive introduction to network flows provides an integrative view of theory, algorithms, and applications. It offers in-depth and self-contained treatments of shortest path, maximum flow, and minimum cost flow problems, including a description of new and novel polynomial-time algorithms for these core models. For professionals working with network flows, optimization, and network programming.

Customer Reviews:

the best network flow book for computer scientists.......2004-12-18

I've been using this book as the primary text for my class in
"Network Flow Programming" (senior & graduate level) at the
University of Tennessee for about 10 years. Prior to that time
I had used Jensen & Barnes' Network Flow Programming (now long out
of print). The code in Jensen & Barnes is in FORTRAN (not so fun
or useful for CS majors) and the intended audience seemed to be OR.
Ahuja's code is pascal pseudo-code for the most part, which usually
translates easily into the C language that most of our students
use.

For CS students, there is excellent use of algorithm analysis
(big-O) throughout the book, and there are long discussions
about different approaches and algorithms and the complexity of
each. There is a lot of mathematical notation, but my students
have never had to worry about PDEs and the like here. Any good
advanced CS student (graduate or undergraduate) will find the
book very worthwhile. In my course the students must implement
min-cost spanning trees, shortest paths, critical path/PERT
networks (not in Ahuja), max flow, and min-cost flow. I would
also recommend (for CS majors) Tarjan's excellent (and
succinct) Data Structures and Network Algorithms.

Good Introductory Book .......2004-12-13

This is a good introductory book. I particularly liked the applications of the problems, introduced in the book. The main negative point that I could mention is, the redundant explanations and discussions you might see in different chapters. I would say the volume of the book could have been reduced by some 15%-20%, if the authors had chosen to be more concise.
The book, Combinatorial Optimization by William J. Cook, et al, is an alternative. It covers a whole lot of topics and is just too succinct, a little more elaboration would have been appreciated !

Great book for Network Theory and Application.......2003-09-25

This book contains a lot of great algorithms for network flow theory and it also contains many of the great applications, which are very useful in practice. This book is very completed. Personally, I learn a lot of new things about Multi commodity Flow, which are the use of Lagrangian Relaxation, Column generation, Resource allocation techniques for solving multi commodity flow. There are also the good chapters in Convex cost flow and Generalized Flow and good appendix in complexity. Beside this book is very easy to read and understand. It is a great idea to have if you are in OR or IE major. :)

Great book for Network Theory and Application.......2002-08-01

PLEASE, write a corrected edition!.......2002-02-28

First of all, I am not surprised that the book
got so many good reviews: at first look, it is truly
impressive, and it is clearly a work of love. I was
looking forward to teaching from it.

It is quite clear from the reviews though, that the
reviewers have not **used** it for teaching; they may
have browsed it at most.

The first disappointments came very soon in the course I
taught. The biggest flaw of the book is the really bad style
in which the proofs are written. They manage to be seemingly
overflowing with explanation, and at the same time difficult
to understand. They gloss over many details: if the teacher
tries to skip these, an alert student could easily make
him/her look pretty silly.

One case in point is the proof of the label correcting
algorithm's correctness starting on page 136. I knew this
material from before, so I thought preparing class from
here would be a breeze. I was wrong: after going back to
my notes, and breaking up the mess into several simple
claims did I manage to make notes from which I could teach.
Whoever missed the class was helpless, when they looked
for explanation in the book.

I only remark, that all classes that I taught from this book
were at some of the top 10 OR depts at the US... so this is
hardly the students' fault.

Many exercises are wrong as well, and although the authors
claim that they will try to fix the mistakes, they hardly ever
reply to reader's comments, as some of my fellow professors
told me.

I can only compare the style of the exposition to the
later written Combinatorial Optimization book by
Cunningham et. al. There is a WORLD of difference.
One can try to look up for instance, the proof
for the label correcting algorithm: the proof in the
Ahuja et. al book is practically creaking at the joints,
while in Cunningham et. al. it flows lucidly.
I suspect that the authors of the latter book wrote it, since
they were unhappy with this one; one can hardly be surprised.

On the positive side, the plethora of applications presented
is truly amazing, and the exercises (when correct) are excellent.

To sum it up: A good book, which could have become a great one,
but have not; one which is very useful, but at the
same time very hard to use... I think the community would thank
the authors for a second, revised edition, that would fix
all the mistakes, and all those terrible proofs.

A final word: this text received the prestigious Lanchester
prize. One may surmise that giving prizes to a textbook
would be best done maybe after 5 years, after a book proved
its worth in actual teaching in the trenches,
so to speak, and NOT based on the first impression that the
jury gets.

Average customer rating:

Fantastic intro book

Great introductory text!

Great Introduction to Algorithmic Design

One of the better introductions

An Interestingly Different Approach

Introduction to the Design and Analysis of Algorithms (2nd Edition)
Anany V. Levitin
Manufacturer: Addison Wesley
ProductGroup: Book
Binding: Paperback

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The Algorithm Design Manual

Algorithm Design

Operating System Concepts

Introduction to Algorithms

Computer Organization and Design, Revised Printing, Third Edition, Third Edition: The Hardware/Software Interface (The Morgan Kaufmann Series in Computer ... Series in Computer Architecture and Design)

ASIN: 0321358287

Book Description

Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a truly innovative manner. Written in a reader-friendly style, the book encourages broad problem-solving skills while thoroughly covering the material required for introductory algorithms. The author emphasizes conceptual understanding before the introduction of the formal treatment of each technique. Popular puzzles are used to motivate readers' interest and strengthen their skills in algorithmic problem solving. Other enhancement features include chapter summaries, hints to the exercises, and a solution manual. For those interested in learning more about algorithms.

Customer Reviews:

Fantastic intro book.......2006-09-27

Even though this book is only a few years old, it seems like a well-worn classic. That is not to say that it is outdated and irrelevant; it is exactly the opposite! While my knowledge of algorithms textbooks isn't encyclopedic, I can say that this book was way ahead of the curve in it's layout. Before it, most books presented a bunch of algorithms with some loose affiliations such as being search algorithms or dealing with graphs. This book groups algorithms into major themes and makes it much easier to learn the fundamentals of algorithm design. There have been a new set of algorithms textbooks coming out as late (Kleinberg and Tardos, Dasgupta et al, etc) that have the same approach as this book because it works so well. Don't miss out!

Great introductory text!.......2006-03-10

For those of you who've always wanted to throw the Cormen text out the window rejoice you finally can! This book is an excellent introduction to algorithms. Though not as thorough as the Cormen text it's orders of magnitude more readable!

Great Introduction to Algorithmic Design.......2005-05-09

I recently finished using this book for a course. I found it to be very well written and the presentation was excellent. Most books on algorithms are hard to read and overly mathematical. This book emphasizes more the textual explanation of algorithms for practical applications and not as much on theoretical proofs etc. The exercises at the end of the chapters strongly reinforce the contents and insightful hints to every exercise are given at the end of the book. I thoroughly enjoyed using this book and found it challenging. Other books I used for reference such as the MIT classic Introduction to Algorithms was also useful but much more difficult to understand initially.

One of the better introductions.......2005-03-12

This book presents the field of algorithm analysis from a different perspective. This book attempts to provide you with enough foundation to not only pick common sorting, searching, etc., algorithms for a problem, but shows you how to design new algorithms if need be. The book is an introduction, so keep that in mind. But the foundation it paves should last you a lifetime.

An Interestingly Different Approach.......2003-06-04

The definitive books on algorithms are widely
acknowledged to be those by Donald Knuth, "The Art of
Computer Programming". Very detailed, and with
voluminous problem sets, they have been the standard
for decades.

Along comes this book with its claim of a different
and complementary classification of the field. The
traditional way is, from a top-down vantage, that at
the highest level, you descend from the root to the
various main problem types. Beneath each problem node
would be subclassifications based on the techniques
used to attack that problem. (I could say "solve", but
that is certainly not the case for some problems.)
This is the most natural classification, because you
often get a problem put in front of you, and you start
from there. Problem-driven.

But what if a method to attack problem A and a method
to attack problem B were very similar? Is there a way
to combine these method nodes? In the problem-driven
tree, not really. So what the author suggests is a
method-driven tree, where problems are descendents of
a method. You regard solutions or research into
problems as instantiations of a particular method.
Sound familiar? You can draw analogies with physics,
if you map the methods into the laws of physics. We
should not follow this too literally. But seen from
this vantage, the author's idea is very reasonable. In
physics, the solutions to a problem are (ideally,
anyway) derived ultimately from the laws of physics.

We should not draw a contrast between the author's
suggestions and the prevailing approach too sharply.
At the research level, a competent analyst should be
aware of different problem areas from which solutions
could be drawn, or to which a solution might be
adapted. As a practical matter, it comes down to the
difference in emphasis for most, rather than a
different worldview.

Customer Reviews:

An okay book!.......2007-05-23

It is just an okay book, not extraordinary in any way. Especially, this is certainly not for the novice in this topic, i.e., it is certainly not a good introductory book. So if you are new to data structures and algorithms, stay away from this book, go for some good introductory book.

For the advanced readers, it is an okay book. Better books are available, e.g., books by Cormen et al. and Robert Sedgewick.

The book is written in a way not very intersting or engaging. The algorithms are not explained in detail. Often things are left unexplained or assumed that the reader already knows it. Algorithms are presented in pseudocode, which causes problems especially for the readers familiar to some particular programming language.

Excellent Book.......2007-05-17

This book explains very clearly the subjects of data structures and algorithms. Its in-depth coverage is very intuitive and easy to follow unlike other literature that is often tedious or esoteric.
The only complaint I have is the choice of the programming language. Pascal is a language of the past. A new edition using C will make this book simply a gem.

A JEWEL.......2006-01-15

Perfect book. Nice and small. You can buy it cheap too, it's old. But it's full of the meat and potatoes, no fluffy Java source code. Sure, it uses Pascal, but it's not that hard to understand Pascal code even if you never programmed in Pascal (me neither). What matters is the discussions behind the scenes. It covers the whole range of what you should know and it's concise. They don't write books like this anymore.

A classic text book on Data Structures........2005-05-19

I believe two books make a classic collection in data structures - one was the data structures book by sartaj sahni (his first edition book many years ago - I haven't looked at his recent books). That was the book I had to study when I was an undergrad student. Now I was entrusted with the task of teaching Data Structures and after looking at several books, this is the one I chose (may be because it comes most close to the style of teaching using psuedo-pascal that I grew up with).

I believe psuedo languages are the best way to learn concepts of any computer science area without getting bogged down in the nitty gritty of a language's syntax and semantics. I found the problems at the end of the chapters to be thoughtful and not extremely hard for undergraduate students. This book also goes into brief mathematical aspects of analysing the complexity of algorithms where necessary. The mathematical analysis is usually the part that most undergrad students moan and groan about, but they better get used to it IMO, if they wish to elevate themselves from the ranks of "a programmer" to an software / algorithm designer.

I have to agree that this book can be extremely hard for the weaker students in the class who have never had any programming or basic college algebra exposure. For all others, this book should be great.

The best introduction to the field - a pleasure to read.......2002-02-10

A textbook by Aho/Hopcroft/Ullman is sort of a guarantee of quality -
and this one is no exception. These people are among the greatest
researchers and teachers in Computer Science, and this book is a
great opportunity to 'learn from the masters'.

As an introduction to the fascinating field of Data Structures and
Algorithms, this is perhaps the best textbook you'll find out there.
Starting with the basics, the authors develop the concepts in a
natural manner. Array, lists and stacks soon give way to binary trees,
heaps and then more advanced data structures. All data structures are
introduced with proper motivation in terms of the kind of problems
that they are useful in solving.

The basic algorithms in searching, sorting, and graphs are then presented
in detail, followed by a chapter on algorithm analysis techniques, and
one on design paradigms such as dynamic programming, backtracking, divide
and conquer, greedy approach, and local search. The book ends with chapters
data structures and algorithms for external storage and memory management.

This is a textbook, and therefore you can expect a fair amount of maths
in the analysis of algorithms, without which you can only do hand-waving.
All algorithms are explained, with detailed examples and illustrations -
this is one of the easiest books to follow in theoretical computer science.

All algorithms are presented in pseudocode, which makes it easier to
understand things at an abtract level without getting bogged down in
language specific technical details, and the pseudocode is very clear
and concise, making it an easy task to adapt it to any given language.

An additional plus-point is its size - weighing in at less than 450
pages, this is a 'backpack friendly' book which you can easily carry
around, unlike many others on the subject.

The only caveat is that the book is almost 20 years old, so you won't
find the more recent topics like red-black trees, skip lists etc.
I'd suggest using this book for an introduction to the basics, with the
book by Cormen et al (if you want the maths) or Sedgewick (if you don't
want the maths) as excellent supplements as well as advanced references.

Book Description

This is the first comprehensive introduction to Support Vector Machines (SVMs), a new generation learning system based on recent advances in statistical learning theory. Students will find the book both stimulating and accessible, while practitioners will be guided smoothly through the material required for a good grasp of the theory and its applications. The concepts are introduced gradually in accessible and self-contained stages, while the presentation is rigorous and thorough. Pointers to relevant literature and web sites containing software make it an ideal starting point for further study.

Customer Reviews:

More for mathematicians than computer scientist.......2006-09-20

This book introduces the concepts of kernel-based methods and focuses specifically on Support Vector Machines (SVM). It is hard to read and a good background in mathematic is clearly needed. The book has a strong emphasis on SVM starting from the very first line of text. Concepts are well explained, although equations are not clear. The notation doesn't facilitate the reading at all. The book covers linear as well as kernel learning. The kernel trick is well described. It is easy to understand ideas behind SVM while reading the corresponding chapter. Finally a small chapter on SVM applications is proposed. Unfortunately, it only contains typical SVM applications (i.e. standard problems).

I think this book is good if you:

* Have a strong mathematical background
* Work in the specific domain of SVM (or kernel-based methods in general)
* Want to write a research paper about SVM and need the correct notations

However, this book is NOT intended for people who:

* Don't like to read theorems, corollaries and remarks
* Are not interested in reading hundreds of proofs

This is my personal opinion as a computer scientist: this book is definitely written for mathematicians.

A little dry........2006-01-09

The book is a little dry at times. Also, I didn't get a very clear idea of how to select kernel functions, which seems pretty important.

Not even close to an intro..........2004-03-21

Oh Puhleeeezzzzz... How is your vector math??? Remember your linear algebra well? Do you have a background in SVM's? Intuitively able to suck out of thin air the meaning of the Gamma co-efficient as applied to svm's?? You've read all the background papers and remember your formal logic???? No?? too bad..your out of luck..

This book is more aptly titled an Introduction to the Formalisms of SVM's. If your a software engineer trying to implement one of these, forget it.. Be nice if they put that quadratic algorthim psuedocode into something more readable than greek symbology..

If you are trying to build one of these engines, then this book is of absolutely no help, unless you have a background in machine learning and have read all the papers on SVM's. If you can decompose the math into code in your head, then you might find it entertaining... What I don't get is how all the rest of these reviewers can give such "glowing praise" for this book and have it be so completely worthless as an introduction... makes me think some of these are shills..

Bottom line is, if your trying to code a svm, this book will not help. If your trying to understand how to implement a svm, this book will not help. If you are trying to understand how an svm works, this book will not help. If you want to know the mathematical basis for SVM's and like that presentation.. this is the book for you..

Excellent book.......2003-11-19

I just happened to read the reviews on the book on Support vector machines by Nello Cristianini and John Shawe-Taylor. Could not resist adding my own comments about the book. Excellent book. I plan to use the book for the course on "Fundamentals of computer aided engineering" that I teach at the Swiss Federal Institute of Technology, Lausanne (EPFL).

This is it !.......2001-08-31

The book is just great. The appendix on algorithms could have more explanations. Also the application section is a short. It would have been more usuful to take one of these applicaitons and describe it in details. But all in all, the book is excellent.

Algorithm Design: Foundations, Analysis, and Internet Examples

Average customer rating:

Egh! Good science bad english
An excellent textbook
A good introduction text to algorithms
Good Fundamentals

Algorithm Design: Foundations, Analysis, and Internet Examples
Michael T. Goodrich , and Roberto Tamassia
Manufacturer: Wiley
ProductGroup: Book
Binding: Paperback

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ASIN: 0471383651

Book Description

Michael Goodrich and Roberto Tamassia, authors of the successful, Data Structures and Algorithms in Java, 2/e, have written Algorithm Engineering, a text designed to provide a comprehensive introduction to the design, implementation and analysis of computer algorithms and data structures from a modern perspective. This book offers theoretical analysis techniques as well as algorithmic design patterns and experimental methods for the engineering of algorithms.
Market: Computer Scientists; Programmers.

Customer Reviews:

Egh! Good science bad english.......2006-10-25

I'm a grad. student using this book, and understanding the written language amounts to same sensation as you would get during root canal. While examples are concise, pseudo-code is excellent, despite the few actual examples in Java, it covers vast range of topics rather well. But for crying out loud, hire an editor for the next edition that will break down paragraph long sentences and introduce some readability to the text! For that reason I tend to gravitate to my undergrad books for my current studies.

An excellent textbook.......2005-03-15

After researching a variety of alternatives, I settled upon using Algorithm Design by Goodrich and Tamassia to teach a junior-level algorithms course and the experience has been quite positive.

While instructor material grows a bit sparse in the last half or third of the book, it's still quite useful. The slides are great and many of the problems have solutions available. Moreover, the solutions tend to be correct (I've only found two mistakes, which may be covered in the up-to-date errata).

The layout of the sections and chapters is quite natural and easy to adapt to your own course, although the last third of the book is essentially an assortment of topics that didn't fit in anywhere else. I would advise bringing some of those topics in to the course early on as diversions from the main material, which admittedly can get a little dry.

For the most part, the book is well written with interesting and adequete end of chapter problems. There are relatively few Java-based examples, but we skipped over them anyhow -- the pseudo-code is quite acceptable. Goodrich and Tamassia give a broad survey of topics, but cover them in enough depth and with enough rigor for an undergraduate course where CLR(S) would be overkill. I recommend it.

A good introduction text to algorithms.......2002-12-18

I would not consider this book as the ultimate book for algorithms as the title suggests. :-) However, it is a very readable book, and filled with brief, but concise observations. Do not get me wrong. This book also has very detailed explanations of fundamental data structures and algorithms.

Also, the best part of the book is that it lists good references for further readings. I loved this book. I would suggest this book to others. Math hints at the back of the books are useful, and some excercises are quite brain challenging. I think it is a great practice for students, but it is not so fun when students get it for assignments. :-)

Good Fundamentals.......2002-07-01

There are many good books with this title or similar ones. This is probably one of the better ones for your bookshelf and for use in academia. The examples are written in Java (a current language) and they are easy to read. The presentation is clean and illustrative. The authors have a good track record for expertise and papers published, and you get the sense that it is more real-world than most similar books.

Practical Algorithms for Image Analysis: Descriptions, Examples, and Code

Average customer rating:

More of a toolbox than a textbook
Good handbook for practitioners
Image Analysis Book Review
It's just great
Luis J Gutierrez

Practical Algorithms for Image Analysis: Descriptions, Examples, and Code
Michael Seul , Lawrence O'Gorman , and Michael J. Sammon
Manufacturer: Cambridge University Press
ProductGroup: Book
Binding: Hardcover

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ASIN: 0521660653

Book Description

This book offers guided access to a collection of algorithms for the digital manipulation and analysis of images. Written in classic "cookbook" style, it reflects the authors' long experience as users and developers of image analysis algorithms and software. For each task, they present a description and implementation of the most suitable procedure in easy-to-use form. The algorithms range from the simplest steps to advanced functions not commonly available for Windows users. Each self-contained section treats a single operation (histogram evaluation, low-pass filtering, and edge detection, among others). The coverage includes typical situations requiring that operation and then discusses the algorithm and implementation. Sections start with a header illustrating the nature of the procedure through a "before" and "after" pictorial example and a ready-reference that lists typical applications, keywords, and related procedures. Annotated references can be found at the end of each section. An accompanying CD-ROM contains a collection of C programs for carrying out the book's procedures.

Customer Reviews:

More of a toolbox than a textbook.......2007-04-07

I already knew image processing when I bought this book, so I am not sure how it would appear to the novice seeking a textbook on the subject of image processing and analysis, but I imagine it could be somewhat confusing. I always recommend Gonzales and Wood's "Digital Image Processing" for those seeking a clear read on image processing and analysis from the ground up. Where Seul's book comes in is with clear descriptions and working code for many basic - and some not so basic - image processing and image analysis algorithms. The book is also very good at explaining the applications of the various transforms. One of the little things that the author of this book does that authors of other books similar to it don't bother to do is to realize that when you are working in image processing you likely have an image as an input and you want an image as an output. Thus the author has built his code libraries so that they work that way. You are not left with arrays of pixels that you have to figure out how to store and manage. In the end you have a nice functional toolbox of working image processing and analysis subroutines that you can chain together and make just about any type of image transform tool you could think of. I'm mainly interested in image effects, and I know this book has been useful to me. The accompanying CD-ROM contains all of the C source code for the algorithms so that you can port them to another language or tinker with them if you so desire. Highly recommended.

Good handbook for practitioners.......2007-01-30

The title of this book corresponds to its content, the tutorial gives an excellent overview of basic key points to those readers who are unfamiliar with the subject (as I was). The book can not be used for rigorous study of even simple things but rather kicks you with essentials that are easy to understand with high-school background. This book, written for non-specialists in "image field", gives them techniques for their practical needs and concentrates exactly on image analysis, not on image processing. If you have no time to go through more complex (and deeper) books, take this one to discover basic principles in short form with no attempt to explain the fundamentals. The authors just put you into the facts, so that is why I would characterize the "Practical Algorithms" book as being "handbook". The good point is that the areas of applicability of these facts are explained, the drawback: you have to go to other books to get more details on image processing roots, e. g., to R. Gonzalez and R. Woods' "Digital Image Processing". I bought both, and use them as good annex to each other. The "Practical Algorithms" has lack of some significant areas, like snake algorithm and image binarization (thresholding) techniques but e.g., the cellular processing is quite well highlighted.
Surprisingly, the CD that comes along with this book gave me almost 80% examples that I was able to recompile instantly, and only several examples have failed, mainly due to image file format issues. The source code is not both elegant and bugless, but it is very transparent and portable and can easily fit, e.g., a 16-bit microcontroller.
Overall, this is good book for fast start. You can get real output and pick up ideas on practical side of image analysis. Just remember, the most book examples came from the medicine world, so they are quite specific and may not be implemented directly in your particular application.

Image Analysis Book Review.......2004-12-06

I found the book to be very informative and I acquired several ideas from reading it. But, I repeatedly found myself searching the book for definitions of some of the terms it uses throughout its text. Practical Algorithms for Image Analysis will introduce new terms without any hint of their meaning, assuming that the reader already knows all they need to know about the subject matter (which would negate the need to buy the book!). This book sorely needs a glossary.

It's just great.......2002-10-15

The book is just great! I used the source code from the CD-ROM for various image processing projects. The algorithms are also very practical if you have to deal with images. The code is neat and ready to compile and run.

Also this book is good on the description of image process and image analysis algorithms. I read the whole book and use it as a reference during my programming. It sits in my bookshelf and I use it almost everyday.

I recommend anybody who wishes to do serious image programming to have this book. It's just great!

Luis J Gutierrez.......2001-04-22

Excelente libro. hace un tiempo que he estado estudiando y desarrollando estrategias para la implementación de sistemas de vision computarizada. Este libro es de una gran claridad práctica sin abandonar la necesaria base teorica. Muy buenos ejemplo, información adicional, ejemplos y aplicaciones. Para cualquier investigador en el área debe ser considerado como un recurso indispensable. (if you want my comments in english please send me an e-mail to innovacl@vtr.net)

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