Notes for the course will be posted here. Let me know if you find any typos or you have any feedback about them!
Overview
Convex optimization
Optimization algorithms
Sparse linear models and denoising
Random projections and compressed sensing
Super-resolution
Sparse regression
Learning representations
Low-rank models