"Lec 21 - Convex Optimization II (Stanford)" Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues subgradients. This course introduces topics such as 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. Complete Playlist for the Course: http://www.youtube.com/view_play_list?p=3940DD956CDF0622 EE 364B Course Website: http://www.stanford.edu/class/ee364b/courseinfo.html Stanford University: http://www.stanford.edu/ Stanford University Channel on YouTube: http://www.youtube.com/stanford
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Tags: Math Technology Algebra calculus geometry electrical engineering convex optimization subgradient derivatives basic inequality function algorithms stepsize rules convergence results proofs optimal step size alternating projections
Duration: 67m 27s
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