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.