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: