Optimization 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.
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