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Convex Optimization, With Corrections 2008
Download Convex Optimization, With Corrections 2008
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Review
"Boyd and Vandenberghe have written a beautiful book that I strongly recommend to everyone interested in optimization and computational mathematics: Convex Optimization is a very readable and inspiring introduction to this modern field of research...The book will be accessible not only to mathematicians but also to researchers and students who want to use convex optimization in applied fields like engineering, computer science, economics, statistics, or others. I recommend it as one of the best optimization textbooks that have appeared in the last years." Mathematical Methods of Operations Research"...this concisely writen book is useful in many regards: as a primary textbook for convex optimization with engineering applications or as an alternate text for a more traditional course on linear or nonlinear optimization." Journal of the American Statistical Association, Hans-Jakob Luethi, Swiss Federal Institute of Technology Zurich"The book by Boyd and Vandenberghe reviewed here is one of ... the best I have ever seen ... it is a gentle, but rigorous, introduction to the basic concepts and methods of the field ... this book is meant to be a 'first book' for the student or practitioner of optimization. However, I think that even the experienced researcher in the field has something to gain from reading this book: I have very much enjoyed the easy to follow presentation of many meaningful examples and suggestive interpretations meant to help the student's understanding penetrate beyond the surface of the formal description of the concepts and techniques. For teachers of convex optimization this book can be a gold mine of exercises." MathSciNet
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Book Description
Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.
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Product details
Hardcover: 727 pages
Publisher: Cambridge University Press; 1 edition (March 8, 2004)
Language: English
ISBN-10: 0521833787
ISBN-13: 978-0521833783
Product Dimensions:
10 x 1.6 x 7.8 inches
Shipping Weight: 3.8 pounds (View shipping rates and policies)
Average Customer Review:
4.4 out of 5 stars
44 customer reviews
Amazon Best Sellers Rank:
#53,181 in Books (See Top 100 in Books)
I think this is the best book for getting into optimization. It's simple with many examples and figures. Excellent choice for engineers, mathematicians might find it incomplete, but what can we do, that's life. I think the interior point section could have had more, but it is still ok. The next step after this book is Nemirovski's book "Lectures on Modern Convex optimization". You can download it for free from his website [...] along with many other notes. Nemirovski's book is very complete and has very modern ideas new to many engineers. But as I said Boyd's book is where you should start from. From an engineer's perspective I believe Boyd's book is much more easy to read and understand than Bertseka's book Convex Analysis and Optimization. I also appreciate Boyd's courtesy to have his book available on-line for free. I bought the book after downloading it because it is worth its price. Try also another book coming from Stanford, which is more specialized Convex Optimization & Euclidean Distance Geometry, also available on-line
Good book!
Quite simply, this is a wonderful text. Coupling this with Boyd's course at Stanford (the lecture videos, HWs, etc. are all available for free online), you're bound to learn quite a lot about optimization. But most importantly, you'll have an idea of when you can actually apply convex optimization to solve a problem that comes up in your particular field.My reasoning in giving it such praise is my preference for the rather unusual methodology it takes in introducing you to optimization. Most books I have seen on linear programming or non-linear programming tackle a few standard problems, introduce what is necessary in terms of definitions and proofs, and then focus on the algorithms that solve these standard problems (conjugate gradient et. al.), how they work, their pitfalls, etc. While this is undoubtedly useful material (which Boyd does cover for a good deal in the final chapters), the simple fact of the matter is these algorithms are available as standard methods in optimization packages (which are abstracted from the user), and unless you are actually going into developing, implementing and tweaking algorithms, this quite honestly is useless.What this book attempts to do, and does very well in my opinion, is to teach you to recognize convexity that's present in problems that are first glance appear to be so incredibly removed from optimization that you might never consider it. This book spends the first 100 pages or so just devoted to building a "calculus" of convexity, if you will, so that you know through what operations convexity is preserved, and you develop intuition as to the potential to use convex optimization in problems in your particular field or application. As such, the first part of the books is focused on building up the skill set, the second part to applications of convex programming, and only the third to the actual algorithms.A word of warning: some of the explanations (especially in Chapter 4 which focuses on types of convex programs and equivalence of programs) are very general, which won't be satisfying to certain readers who need solid examples to reinforce the concepts. Also, a lot of the material can be quite challenging, requiring a bit of mental gymnastics. However, if you are accompanying your study with the problems at the end of each chapter, you're certain to get practice and demystify the concepts.In sum, all things considered, a great text.
This material is somewhat tangential to my research, but I learned a ton by reading it. Very well organized.For example, here is a problem I was working on. For a given matrix A, find vectors a and b such that1. |A| <= ab^T, (outer product) and2. a^Tb (inner product) is a minimum. Convex Optimization showed me how to convert this into a CO problem
This is an excellent text on optimization. The pdf version is free on the net. First I got the pdf version, I like the writing style and the way authors have described the concepts. Then I ordered the hard print. The print quality is excellent and its a great book to have!
This book is great! The writers tend to capture the theory of convex optimization in a concise way and further illustrate it by showing their applications. The book also has a rigorous set of exercises.
Fantastic, pedagogical book. Also there are video lectures online
Excelent book. Second to none on Convex Optimization problems.
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