Saddle-Point Interpretation, KKT Conditions & Perturbation
Samsung Professor in the School of Engineering
Derives Karush-Kuhn-Tucker optimality conditions, complementary slackness, and shadow-price sensitivity analysis ∂p*/∂uᵢ = -λᵢ*.
Professor Stephen Boyd, of the Stanford University Electrical Engineering department, continues his lecture 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.
The Lagrangian, Dual Function & Slater's Condition
Next · Lecture 7Geometric Interpretation of Duality, Sensitivity & Theorems of Alternatives
