Convex Optimization II
Free, no sign-up neededArchived courseEnglish
About this course
Continuation of Convex Optimization I. Subgradient, cutting-plane, and ellipsoid methods. Decentralized convex optimization via primal and dual decomposition. Alternating projections. Exploiting problem structure in implementation. Convex relaxations of hard problems, and global optimization via branch & bound. Robust optimization. Selected applications in areas such as control, circuit design, signal processing, and communications. Course requirements include a substantial project.
Description from Stanford Engineering Everywhere.
Where to take this course
- Open Stanford Engineering Everywhere (new tab)Stanford Engineering Everywhere · Archived course