"Lec 34 - Convex Optimization II (Stanford)" Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd continues lecturing on L1 Methods for Convex-Cardinality Problems. 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. EE 364B Course Website: http://www.stanford.edu/class/EE364B/courseinfo.html Stanford University: http://www.stanford.edu/ Stanford 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 functions algorithms newtons method extensions truncated interior-point methods dual rate control cardi
Duration: 62m 58s
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