Convex Optimization II

Course Description


Continuation of 364a. 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.



Tags: Math, Math Calculus

Convex Optimization II

Prof. Boyd in lecture 7: "Ellipsoid Methods".
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