## 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 6-10 of 32

1.2 Symmetric Matrices Throughout most of this book our setting is an abstract

**Euclidean space**E. This has a number of advantages over always working in R”:

the basisindependent notation is more elegant and often clearer, and it ...

Corollary 2.1.3 (First order conditions for linear constraints) For a convex set C c

E, a function f : C – R, a linear map A: E → Y (where Y is a

**Euclidean space**) and

a point b in Y, consider the optimization problem inf{f(x)|x e C, Ax = b}. (2.1.4) ...

(Normals to affine sets) Given a linear map A : E → Y (where Y is a

**Euclidean**

**space**) and a point b in Y, prove the normal cone to the set {a e E Ax = b} at any

point in it is A*Y. Hence deduce Corollary 2.1.3 (First order conditions for linear ...

(Nearest polynomial with a given root) Consider the

**Euclidean space**of complex

polynomials of degree no more than n, with inner product 71. - 7. • 7% (XX,” ?

XXuz') : XXiu. j=0 j=0 j=0 Given a polynomial p in this space, calculate the

nearest ...

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### Contents

15 | |

Fenchel Duality | 33 |

Convex Analysis | 65 |

Special Cases | 97 |

Nonsmooth Optimization | 123 |

KarushKuhnTucker Theory | 153 |

Fixed Points | 179 |

Infinite Versus Finite Dimensions | 209 |

List of Results and Notation | 221 |

Bibliography | 241 |

Index | 253 |

### Other editions - View all

Convex Analysis and Nonlinear Optimization: Theory and Examples Jonathan M. Borwein,Adrian S. Lewis No preview available - 2000 |