| 
w   b
Course

Convex Optimization II

Stanford University

Continuation of Convex Optimization I. Topics include: 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.

Continue Reading ▼
Home > Mathematics > Calculus > Convex Optimization II Lectures: