Stanford EE364a Lecture 2: Affine Sets, Convex Sets, Cones & Hyperplanes
Samsung Professor in the School of Engineering
Builds geometric fluency over polyhedra, norm balls, ellipsoids, positive semidefinite cones S₊ⁿ, and operations that preserve convexity.
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.
Mathematical Optimization & Why Convexity Is the Watershed
Next · Lecture 3Stanford EE364a Lecture 3: Convex Functions — First/Second-Order Conditions & Epigraphs
