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Convex Optimization by Stephen Boyd
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- ¡Cómpralo ya!Convex Optimization by Stephen Boyd
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USD3,99 (aprox. 3,42 EUR) USPS Media MailTM.
Ubicado en: Nashville, TN, Estados Unidos
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Entrega prevista entre el sáb. 16 ago. y el jue. 21 ago.
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N.º de artículo de eBay:394185223931
Última actualización el 12 ago 2025 16:14:52 H.EspVer todas las actualizacionesVer todas las actualizaciones
Características del artículo
- Estado
- Publish Year
- 2004
- ISBN
- 9780521833783
Acerca de este producto
Product Identifiers
Publisher
Cambridge University Press
ISBN-10
0521833787
ISBN-13
9780521833783
eBay Product ID (ePID)
6048789
Product Key Features
Number of Pages
727 Pages
Publication Name
Convex Optimization
Language
English
Subject
Linear & Nonlinear Programming, Optimization
Publication Year
2004
Type
Textbook
Subject Area
Mathematics
Format
Hardcover
Dimensions
Item Height
1.6 in
Item Weight
59.3 Oz
Item Length
10 in
Item Width
7.8 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2003-063284
Reviews
'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 introduction to this modern field of research.' Mathematics of Operations Research, 'I highly recommend it either if you teach nonlinear optimization at the graduate level for a supplementary reading list and for your library, or if you solve optimization problems and wish to know more about solution methods and applications.' International Statistical institute, '… the whole book is characterized by clarity. … a very good pedagogical book … excellent to grasp the important concepts of convex analysis [and] to develop an art in modelling optimization problems intelligently.' Matapli, '… a beautiful book that I strongly recommend to everyone interested in optimization and computational mathematics … a very readable and inspiring introduction to this modern field of research. I recommend it as one of the best optimization textbooks that have appeared in the last years.' Mathematical Methods of Operations Research, "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, '... the whole book is characterized by clarity. ... a very good pedagogical book ... excellent to grasp the important concepts of convex analysis [and] to develop an art in modelling optimization problems intelligently.' Matapli, '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, '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, "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, 'This book is extremely friendly and helpful to freshmen in optimization, the rich examples demonstrate the concepts well. I believe this is a must read book for everyone, especially those who want an elegant writing style.' Kai Liu, Clemson University, "...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, '... a beautiful book that I strongly recommend to everyone interested in optimization and computational mathematics ... a very readable and inspiring introduction to this modern field of research. I recommend it as one of the best optimization textbooks that have appeared in the last years.' Mathematical Methods of Operations Research
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
519.6
Table Of Content
Preface; 1. Introduction; Part I. Theory: 2. Convex sets; 3. Convex functions; 4. Convex optimization problems; 5. Duality; Part II. Applications: 6. Approximation and fitting; 7. Statistical estimation; 8. Geometrical problems; Part III. Algorithms: 9. Unconstrained minimization; 10. Equality constrained minimization; 11. Interior-point methods; Appendices.
Synopsis
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 book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. 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., Convex optimization problems arise frequently in many different fields. A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text 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., The focus of this 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.
LC Classification Number
QA402.5 .B69 2004
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