Opening book details…
Can I read Convex Optimization Theory on EtoBox?
Convex Optimization Theory by Dimitri P. Bertsekas is a mathematics available to read on EtoBox.
What is Convex Optimization Theory about?
An insightful, concise, and rigorous treatment of the basic theory of convex sets and functions in finite dimensions, and the analytical/geometrical foundations of convex optimization and duality theory. Convexity theory is first developed in a simple accessible manner, using easily visualized proofs. Then the focus shifts to a transparent geometrical line of analysis to develop the fundamental duality between descriptions of convex sets and functions in terms of points and in terms of hyperplanes. Finally, convexity theory and abstract duality are applied to problems of constrained optimization, Fenchel and conic duality, and game theory to develop the sharpest possible duality results within a highly visual geometric framework. The book may be used as a text for a theoretical convex optimization course; the author has taught several variants of such a course at MIT and elsewhere over the last ten years. It may also be used as a supplementary source for nonlinear programming classes, and as a theoretical foundation for classes focused on convex optimization models (rather than theory). It is an ideal companion to the books Convex Optimization Algorithms, and Nonlinear Programming
Who reads Convex Optimization Theory?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Dimitri P. Bertsekas
- Publisher
- Athena Scientific
- Published
- 2009
- Language
- EN
- ISBN
- 9781886529311
- Category
- mathematics
- Subjects
- Technology, Mathematics, Computer Science
- Rating
- 4.6 / 5 (22 ratings)
- Updated
- 2026-03-14
More by Dimitri P. Bertsekas
Browse all works by Dimitri P. Bertsekas
Similar books
- Convex Analysis and Optimization — Dimitri P. Bertsekas, Angelia Nedic, Asuman E. Ozdaglar (2003)
- Convex Analysis and Nonlinear Optimization : Theory and Examples — Jonathan M. Borwein, Adrian S. Lewis (auth.) (2000)
- Convex Optimization Algorithms — Bertsekas D.P. (2015)
- Convex and Stochastic Optimization (Universitext) — J. Frédéric Bonnans J. (2019)
- Convex Optimization — Stephen P Boyd; Lieven Vandenberghe (2004)
- Optimization III. Convex Analysis, Nonlinear Programming Theory, Standard Nonlinear Programming Algorithms — Aharon Ben-Tal, Arkadi Nemirovski (2023)