Lecture 15 | 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

Category:

Education

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