EE 6151 Advanced Topics in Networks (Fall 2014)
*The course number might be changed but the title will remain the same.
Slot: G
Prerequisite: A basic convex optimization course (for example EE5121) which introduces convex functions, optimization, duality and hopefully SDP’s. COT required;
Tentative syllabus:
- Recap of convex optimization
- Convex functions
- Convex problems
- Duality (Conic)
- Complexity bounds
- Unconstrained minimization (smooth convex functions)
- Constrained minimization (smooth convex functions)
- Interior point techniques (smooth convex functions)
- Subgradient methods (non smooth convex functions)
- Subgradients
- Subgradient methods (constrained)
- Stochastic subgradient
- Cutting plane methods
- Ellipsoid method
- Proximal algorithms (large scale optimization)
- FISTA
- Mirror descent algorithm