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Convex Analysis may be considered as a refinement of standard calculus, with equalities and approximations replaced by inequalities. As such, it can easily be integrated into a graduate study curriculum. Minimization algorithms, more specifically those adapted to non-differentiable functions, provide an immediate application of convex analysis to various fields related to optimization and operations research. These two topics making up the title of the book, reflect the two origins of the authors, who belong respectively to the academic world and to that of applications. Part I can be used as an introductory textbook (as a basis for courses, or for self-study); Part II continues this at a higher technical level and is addressed more to specialists, collecting results that so far have not appeared in books.
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Convex Analysis and Minimization Algorithms I: Fundamentals (Grundlehren der mathematischen Wissenschaften Book 305)
May 26, 2011, Springer
3662027968 9783662027967
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September 28, 2024 | Edited by MARC Bot | import existing book |
February 28, 2019 | Created by MARC Bot | import new book |