Gerogia Institute of Technology ECE 6270 course. Refer to http:http://mdav.ece.gatech.edu/ece-6270-spring2021/ if you are interested in mathmatical theory. Note that it's my instructor(Mark Davenport)'s website. And I run all the code on JupyterLab or Pycharm on MAC OS.
This file includes homework, of course includes some codes beyond the homework(Other visualization), and I will keep updating it about some mathmatical theories about convex optimization. Note that all the homeworks have been encrypted, anyone wants to violate GT's Academic Honor Integrity will be punished.
The mainly contains some realization of mathmatical theories about convex optimization. The contents are as follows,
- convex sets
- convex functions
- convexity, gradients, and optimization
- gradient descent
- line search methods
- convergence analysis
- accelerated first order methods (Heavy ball, Neseterov)
- Newton's method
- Quasi-Newton method: BFGS
- Subgradient descent
- Proximal Algorithms
- Geometric view of constrained problems
- Fenchel duality
- Lagrange duality
- Karush-Kuhn-Tucker (KKT) conditions
- barrier techniques
- projected gradient descent
- splitting methods, alternating direction method of multipliers
- ADMM