Convex optimization

By: Boyd, StephenContributor(s): Vandenberghe, LievenMaterial type: TextTextPublication details: Cambridge, UK ; New York : Cambridge University Press, 2004Description: xiii, 716 pages : illustrationsISBN: 9780521833783; 0521833787 Subject(s): Mathematical optimization | Convex functionsDDC classification: 519.3
Contents:
Introduction -- Convex sets -- Convex functions -- Convex optimization problems -- Duality -- Approximation and fitting -- Statistical estimation -- Geometric problems -- Unconstrained minimization -- Equality constrained minimization -- Interior-point methods -- Appendices: A. Mathematical background -- B. Problems involving two quadratic functions -- C. Numerical linear algebra background.
Summary: From the publisher. 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
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Reference Books Reference Books Main Library
Reference 		Reference 519.3 BOY (Browse shelf(Opens below)) Available 009799
Total holds: 0

Bibliography & index

Introduction --
Convex sets --
Convex functions --
Convex optimization problems --
Duality --
Approximation and fitting --
Statistical estimation --
Geometric problems --
Unconstrained minimization --
Equality constrained minimization --
Interior-point methods --
Appendices: A. Mathematical background --
B. Problems involving two quadratic functions --
C. Numerical linear algebra background.


From the publisher. 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

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