EE&CSE: 컨벡스 최적화
This course aims to give students the tools and training to recognize convex optimization problems that arise in scientific and engineering applications, presenting the basic theory, and concentrating on modeling aspects and results that are useful in applications. Topics include convex sets, convex functions, optimization problems, least-squares, linear and quadratic programs, semidefinite programming, optimality conditions, and duality theory. This course should benefit anyone who uses or will use scientific computing or optimization in engineering or related work. More specifically, people from the following departments and fields: Electrical Engineering (especially areas like signal and image processing, communications, control); Aero & Astro (control, navigation, design); Computer Science (especially machine learning, robotics, computer graphics, algorithms & complexity, computational geometry); Operations Research (MS&E at Stanford); and Scientific Computing and Computational Mathematics.