Subgradient Methods for Constrained Problems. 
Subgradient Methods for Constrained Problems.
by Stanford / Stephen P. Boyd
Video Lecture 4 of 20
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Date Added: March 29, 2009

Lecture Description

Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd lectures on subgradient methods for constrained problems.

Course Index

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


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