Convex Analysis and Minimization Algorithms I
Fundamentals
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This book covers the fundamentals of convex analysis, a refinement of standard calculus with equalities and approximations replaced by inequalities. Reviews minimization algorithms, which provide immediate application to optimization and operations research.
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 authors, who belong respectively to the academic world and to that of applications. The approach of their book is very comprehensive without being encyclopaedic: the emphasis is on introducing readers in a gradual and digestible manner to the concepts of convex analysis, their interlinking and their implications, with algorithmic ideas worked in.
Theory is interspersed with application and vice versa; illustrative numerical results are given, and over 170 pictures illustrate and support geometric intuition. Throughout the book, ample comments help the reader further to master the concepts and methods, and to understand the motivations, the difficulties, and the relative significance of results.
Theory is interspersed with application and vice versa; illustrative numerical results are given, and over 170 pictures illustrate and support geometric intuition. Throughout the book, ample comments help the reader further to master the concepts and methods, and to understand the motivations, the difficulties, and the relative significance of results.
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