Lecture 2 | Convex Optimization I (Stanford)

Lecture 2 | Convex Optimization I (Stanford)


Guest Lecturer Jacob Mattingley covers convex sets and their applications in electrical engineering and beyond for the course, Convex Optimization I (EE 364A). Convex Optimization I concentrates on recognizing and solving convex optimization problems that arise in engineering. Convex sets, functions, and optimization problems. Basics of convex analysis. Least-squares, linear and quadratic programs, semidefinite programming, minimax, extremal volume, and other problems. Optimality conditions, duality theory, theorems of alternative, and applications. Interior-point methods. Applications to signal processing, control, digital and analog circuit design, computational geometry, statistics, and mechanical engineering. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=3940DD956CDF0622 EE 364A Course Website: http://www.stanford.edu/class/ee364 Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford/

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