Schedule
Sixteen weeks, two hours each, 32 contact hours in total. Section and page numbers refer to Golub & Van Loan, Matrix Computations, 4th edition. Reading load is roughly 30 pages per week.
Click any week for objectives, algorithms, and materials.
| Wk | Topic | Reading | Theme | Due |
|---|---|---|---|---|
| Foundations | ||||
| 1 | Matrix multiplication as computation | §1.1–1.3 pp. 2–33 |
Cost | — |
| 2 | Vector spaces, norms, and orthogonality | §2.1–2.3 pp. 64–76 |
Language | — |
| 3 |
The singular value decomposition
Key week |
§2.4–2.5 pp. 76–87 |
Structure | — |
| 4 | Sensitivity and finite precision | §2.6–2.7 pp. 87–105 |
Conditioning | Assignment 1 — norms and conditioning |
| Linear systems | ||||
| 5 | Triangular systems and the LU factorization | §3.1–3.2 pp. 106–122 |
Solve | — |
| 6 | Roundoff, pivoting, and accuracy | §3.3–3.5 pp. 122–144 |
Stability | — |
| 7 | Positive definite and banded systems | §4.1–4.3 pp. 154–186 |
Exploit structure | Assignment 2 — LU and Cholesky |
| 8 |
Structured and fast solvers
Midterm |
§4.5, 4.7–4.8 pp. 196–233 |
Exploit structure | Midterm examination |
| Least squares | ||||
| 9 | Householder, Givens, and the QR factorization | §5.1–5.2 pp. 234–260 |
Orthogonality | — |
| 10 | The full-rank least squares problem | §5.3–5.4 pp. 260–288 |
Fit | Assignment 3 — QR and least squares |
| 11 | Rank deficiency, regularization, and total least squares | §5.5, 6.1, 6.3 pp. 288–327 |
Regularize | — |
| Eigenvalues | ||||
| 12 | Eigenvalue theory and perturbation | §7.1–7.2 pp. 348–365 |
Diagonalize | — |
| 13 | Power iterations and the QR algorithm | §7.3–7.5 pp. 365–394 |
Diagonalize | Assignment 4 — eigenvalues |
| 14 |
Symmetric eigenproblems and computing the SVD
Closes the loop from Week 3 |
§8.1–8.3, 8.6 pp. 440–467, 486–497 |
Diagonalize | — |
| Large scale | ||||
| 15 | Sparse systems, conjugate gradient, and preconditioning | §11.1–11.3, 11.5, 10.1 pp. 598–639, 650–670, 546–556 |
Scale up | Assignment 5 — sparse and iterative methods |
| Synthesis | ||||
| 16 | Matrix calculus, backpropagation, and synthesis | §12.3 pp. 707–719 |
Differentiate | Course project presentations |
What is deliberately left out
A 32-hour course cannot cover a 747-page book. These are named in lecture but not examined, and each makes a good project topic:
- Chapter 9, Functions of Matrices — the matrix exponential, sign, square root and logarithm.
- Most of Chapter 10 — beyond the symmetric Lanczos process in Week 15.
- §11.6, The Multigrid Framework — a natural follow-on to Week 15.
- §12.1–12.2, 12.4–12.5 — displacement structure, structured-rank problems, and tensor decompositions.
- Parallel sections (§1.6, §3.6) and the more specialised eigenvalue material (§7.6–7.9, §8.4–8.5, §8.7).