Lecture 1 | Convex Optimization II (Stanford)

Lecture by Professor Stephen Boyd for Convex Optimization II (EE 364B) in the Stanford Electrical Engineering department. Professor Boyd's first lecture is on the course requirements, homework assignments, and then goes into his first topic- 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

Category:

Education

Tags:

• Math
• Technology
• Algebra
• calculus
• geometry
• electrical
• engineering
• convex
• optimization
• subgradient
• derivatives
• basic
• inequality
• function
• algorithms
• analysis
• nondifferentiable
• subdifferential
• weak
• strong

[ttcyt2000]

Thanks to Professor Stephen Boyd for his great video.

[dragonrez]

I watched all of 364A via youtube not knowing what to expect. I found the material immediately applicable to my biomedical engineering projects. Keep up the great work.