Convex Optimization A comprehensive introduction to the tools, techniques and applications of convex optimization. Stephen Boyd (Author), Lieven Vandenberghe (Author) 9780521833783, Cambridge University Press Hardback, published 8 March 2004 727 pages, 337 exercises25.4 x 19.7 x 4 cm, 1.7 kg '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 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. 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. Subject Areas: Computer science [UY], Electronics & communications engineering [TJ], Optimization [PBU], Mathematics [PB], Investment & securities [KFFM], Econometrics [KCH]
