Arkadi Nemirovski

Written by two influential researchers, this engaging textbook provides an accessible yet mathematically rigorous introduction to convex optimization. By excluding modeling and algorithms, the authors are able to discuss the theoretical aspects in greater depth. Its more elementary treatment is based on linear algebra, calculus, and real analysis, thus lowering the background barrier for students in applied mathematics, computer science, and engineering.
Focuses on the mathematical foundations, providing a fresh look at convex analysis from the point of view of optimization while also covering modern topics such as conic programming, conic representations of convex sets and functions, and cone-constrained convex problems ; Provides all you need to know, including detailed proofs, in a concise package ; Engages readers with its conversational tone and hands-on learning opportunities, including over 170 exercises and over 30 "Facts" to prove, aimed to train readers to become active players in optimization, and not just mere consumers of its techniques ; Includes appendices that cover all the prerequisites from linear algebra, real analysis, calculus, and symmetric matrices for the course.