Uploaded by StanfordUniversity on Jul 9, 2008
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.
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
EE364B Course Website:
http://www.stanford.edu/class/ee364b/
Stanford University:
http://www.stanford.edu
Stanford University Channel on YouTube:
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Category:
Tags:
- Math
- Technology
- Algebra
- calculus
- geometry
- electrical
- engineering
- convex
- optimization
- subgradient
- derivatives
- basic
- inequality
- function
- algorithms
- method
- dual
- constrained
- linear
- equality
- constraints
- negativ
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For more information about this license, please read: http://creativecommons.org/licenses/by-nc-nd/3.0/.
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