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Linear Systems and Optimization: Convex Optimization II

Linear Systems and Optimization: Convex Optimization II

Convex Optimization II is one of the ten free courses being offered to the public through Stanford Engineering Everywhere. The course belongs to the Linear Systems and Optimization series and is taught by Professor Stephen Boyd of Stanford University's Electrical Engineering Department.

The course covers 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.

Keywords:
Robust Optimization, Cutting-plane, Circuit Design, Stanford University, Ellipsoid Methods, Global Optimization, Signal Processing, Subgradient, Alternating Projections, Stanford Engineering Everywhere, Dual Decomposition, Primal Decomposition, Stephen Boyd, Convex Optimization, Electrical Engineering
Disciplines:
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More about this material

Material Type:
Online Course
Date Added to MERLOT:
November 21, 2008
Date Modified in MERLOT:
August 3, 2015
Author:
Stanford Engineering Everywhere, School of Engineering, Stanford University  
Submitter:
Christopher Kong
Primary Audience:
College General Ed, College Lower Division, College Upper Division, Graduate School, Professional
Technical Format:
Video
Mobile Compatibility:
Not specified at this time
Technical Requirements:
Lecture videos are offered via Silverlight, iTunes, YouTube, and downloadable .wmv and .mp4 torrents. Course materials in the form of .pdf files are also available for download.
Language:
English
Cost Involved:
no
Source Code Available:
no
Accessibility Information Available:
no
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-ShareAlike 3.0 United States

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