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Convex Optimization

Convex Optimization

£53.00

  • Date Published: March 2004
  • availability: Temporarily unavailable - available from October 2014
  • format: Hardback
  • isbn: 9780521833783

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About the Authors
  • 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.

    • Gives comprehensive details on how to recognize convex optimization problems in a wide variety of settings
    • Provides a broad range of practical algorithms for solving real problems
    • Contains hundreds of worked examples and homework exercises
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    Reviews & endorsements

    '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

    '… 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

    '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

    '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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    Product details

    • Date Published: March 2004
    • format: Hardback
    • isbn: 9780521833783
    • length: 727 pages
    • dimensions: 197 x 253 x 40 mm
    • weight: 1.68kg
    • contains: 337 exercises
    • availability: Temporarily unavailable - available from October 2014
  • Table of Contents

    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.

  • general resources

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    General ResourcesSolutionsSolutions Manualpdf1782KB0solutions general resources solutions general resourcessolutions

    This title has a locked file and access is given only to lecturers adopting the textbook for their class. We need to enforce this strictly so that solutions are not made available to students. To gain access to locked resources you need first to log in with your Cambridge account details and then return to this page to submit details of your course so that you can be authenticated as a lecturer. Click here to log in. If you do not have a Cambridge account you will need first to click here to create an account and then return to this page to be authenticated.


    These resources are provided free of charge by Cambridge University Press with permission of the author of the corresponding work, but are subject to copyright. You are permitted to view, print and download these resources for your own personal use only, provided any copyright lines on the resources are not removed or altered in any way. Any other use, including but not limited to distribution of the resources in modified form, or via electronic or other media, is strictly prohibited unless you have permission from the author of the corresponding work and provided you give appropriate acknowledgement of the source.

    If you are having problems accessing these resources please email cflack@cambridge.org

  • Authors

    Stephen Boyd, Stanford University, California
    Stephen Boyd received his PhD from the University of California, Berkeley. Since 1985 he has been a member of the Electrical Engineering Department at Stanford University, where he is now Professor and Director of the Information Systems Laboratory. He has won numerous awards for teaching and research, and is a Fellow of the IEEE. He was one of the co-founders of Barcelona Design, and is the co-author of two previous books Linear Controller Design: Limits of Performance and Linear Matrix Inequalities in System and Control Theory.

    Lieven Vandenberghe, University of California, Los Angeles
    Lieven Vandenberghe received his PhD from the Katholieke Universiteit, Leuven, Belgium, and is a Professor of Electrical Engineering at the University of California, Los Angeles. He has published widely in the field of optimization and is the recipient of a National Science Foundation CAREER award.

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