This book offers a clear and accessible overview of convex analysis and its applications, targeting first-year graduate students. It includes optional exercises for further learning and features new material on semismooth optimization and additional proofs, enhancing its self-contained nature.
Focusing on convex analysis, this book presents a clear and concise overview of the subject and its applications, aimed at a broad audience, including first-year graduate students. It combines theoretical insights with practical exercises, enhancing the learning experience. The new edition introduces additional content on semismooth optimization and includes new proofs to improve self-sufficiency. With its elegant approach, the text serves as both a teaching resource and a comprehensive reference for those interested in computational optimization techniques.
The revised second edition introduces a new chapter titled "Recent Experiences," showcasing examples of experimental mathematics discovered since 2003. It retains the original content and spirit of the first edition while offering updated insights into the field. This edition serves as an essential resource for those interested in the latest developments in experimental mathematics.