Lecture 7 | Convex Optimization I

Professor Stephen Boyd, of the Stanford University Electrical Engineering department, expands upon his previous lectures on convex optimization problems 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/

Category:

Education

Tags:

• science
• electrical
• engineering
• technology
• convex
• optimization
• generalized
• inequality
• constraints
• minimization
• risk
• return
• eigenvalue
• linear
• matrix
• Pareto
• optimal