Convex Optimization II

Stanford Course , Prof. Stephen Boyd

325 students enrolled

Overview

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 and bound. Robust optimization. Selected applications in areas such as control, circuit design, signal processing, and communications.

Lecture 6: Analytic center cutting-plane method

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