The course material for Spring 2023 is available on the Bruin Learn course website.
1. Matrix rank
2. Positive semidefinite matrices
3. Symmetric eigendecomposition
4. Singular value decomposition
5. Applications to data fitting
6. Geometric applications
7. Spectral clustering
8. Kernel methods
9. QR algorithm
10. Schur decomposition
11. Gershgorin bounds
12. Nonnegative matrices
13. Constrained nonlinear least squares