Convex Analysis and Nonlinear Optimization: Theory and ExamplesOptimization is a rich and thriving mathematical discipline. The theory underlying current computational optimization techniques grows ever more sophisticated. The powerful and elegant language of convex analysis unifies much of this theory. The aim of this book is to provide a concise, accessible account of convex analysis and its applications and extensions, for a broad audience. It can serve as a teaching text, at roughly the level of first year graduate students. While the main body of the text is self-contained, each section concludes with an often extensive set of optional exercises. The new edition adds material on semismooth optimization, as well as several new proofs that will make this book even more self-contained. |
From inside the book
Results 1-5 of 91
... proof technique permitting those readers familiar with functional analysis to discover for themselves how a result ... proofs ; important pieces of additional theory or more testing examples ; longer , harder examples or peripheral ...
... proof is a standard application of the Bolzano- Weierstrass theorem above . Proposition 1.1.3 ( Weierstrass ) Suppose that the set D C E is non- empty and closed , and that all the level sets of the continuous function f : D → R are ...
... proof is outlined in Exercise 10 . Exercises and Commentary Good general references are [ 177 ] for elementary real analysis and [ 1 ] for lin- ear algebra . Separation theorems for convex sets originate with Minkowski [ 142 ] . The ...
... proof of Proposition 1.1.5 . The relative interior Some arguments about finite - dimensional convex sets C simplify and lose no generality if we assume C contains 0 and spans E. The following exer- cises outline this idea . 11 . 12 ...
... proof of this result as an exercise . Proposition 1.2.4 ( Hardy - Littlewood - Pólya ) Any vectors x and y in R satisfy the inequality xTy≤ [ x ] [ y ] . У We describe a proof of Fan's theorem in the exercises , using the above ...
Contents
1 | |
15 | |
Chapter 3 Fenchel Duality | 33 |
Chapter 4 Convex Analysis | 65 |
Chapter 5 Special Cases | 97 |
Chapter 6 Nonsmooth Optimization | 123 |
Chapter 7 KarushKuhnTucker Theory | 153 |
Chapter 8 Fixed Points | 179 |
Chapter 9 More N onsmooth Structure | 213 |
Infinite Versus Finite Dimensions | 239 |
Chapter 11 List of Results and Notation | 253 |
Bibliography | 275 |
Index | 289 |
Other editions - View all
Convex Analysis and Nonlinear Optimization: Theory and Examples Jonathan M. Borwein,Adrian S. Lewis No preview available - 2000 |