Tsinghua Course on Sparse Approximation

Lecture Notes and Assignments

The lectures were recorded and are available on YouTube

Monday October 14
Lecture 1 notes: basis expansion fundamentals

Lecture 2 notes: overview of sparsity theory and applications

Lecture 3 notes: sparse approximation algorithms

Homework 1
You will need the file hw1problem3.mat.

Tuesday October 15

Lecture 4 notes: uncertainty principles for unions of bases

Lecture 5 notes: overview of compressive sensing

Homework 2

Thursday October 17

Lecture 6 notes: L1 minimization: duality and optimality

Lecture 7 notes: L1 recovery with the restricted isometry property

Lecture 8 notes: stability of L1 recovery

Homework 3; you will need the files l1eq_pd.m, Gaussian_Phi.m, SubDCT_Phi.m, and SubToep_Phi.m.

Friday October 18

Lecture 9 notes: the RIP for Gaussian matrices

Lecture 10 notes: low rank recovery and bilinear problems

Lecture 11 notes: dynamic l1 recovery

Homework 4

© 2013 Justin Romberg