2004 ConvexOptimization

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Subject Headings: Convex Optimization Task, Convex Optimization Algorithm.

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Book Overview

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 Convex Optimization Task|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.

Table of Contents

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.

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2004 ConvexOptimizationStephen Boyd
Lieven Vandenberghe
Convex Optimizationhttp://www.stanford.edu/~boyd/cvxbook/bv cvxbook.pdf2004