Convex optimization

By:

Boyd, Stephen

Contributor(s):

Vandenberghe, Lieven

Material type: Text

TextPublication details: Cambridge, UK ; New York : Cambridge University Press, 2004.Description: xiii, 716 pages : illustrationsISBN:

9780521833783
0521833787

Subject(s):

DDC classification:

519.3 BOY

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	Main Library Reference	Reference	519.3 BOY (Browse shelf(Opens below))	Available		009799

Total holds: 0

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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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