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:

  1. Recap of convex optimization
  1. Convex functions
  2. Convex problems
  3. Duality (Conic)
  1. Complexity bounds
  2. Unconstrained minimization (smooth convex functions)
  3. Constrained minimization  (smooth convex functions)
  4. Interior point techniques (smooth convex functions)
  5. Subgradient methods (non smooth convex functions)
  1. Subgradients
  2. Subgradient  methods (constrained)
  3. Stochastic subgradient
  1. Cutting plane methods
  1. Ellipsoid method
  1. Proximal algorithms (large scale optimization)
  2. FISTA
  3. Mirror descent algorithm