Name | Role | Office hours |
|
Ioana Dumitriu | Instructor A00 | idumitriu@ucsd.edu | Wed, 11-12pm, AP&M 5824; Thu, 4:30-6:30pm (Zoom) |
Lei Huang | Instructor B00 | leh010@ucsd.edu | |
Jiyoung Choi | Teaching Assistant A01 and A02 |
jichoi@ucsd.edu | |
Haixiao Wang | Teaching Assistant A03 and A04 |
h9wang@ucsd.edu | |
Shuncheng Yuan | Teaching Assistant B01 and B02 |
syuan@ucsd.edu |
|
Xiaomeng Hu | Teaching Assistant B03 and B04 |
x8hu@ucsd.edu |
|
This is a tentative course outline and might be adjusted
during the quarter. The chapters refer to textbook chapters.
If you see a + next to a
lecture, the lecture contains MORE information than the
respective chapter.
Week | Monday | Tuesday | Wednesday | Thursday | Friday |
---|---|---|---|---|---|
0 |
Sep
29 3.3, 6.1-6.3 (finite precision, big-Oh) |
||||
1 |
Oct
2 3.1+ (triangular systems, Gaussian elimination) |
|
Oct
4 3.1+, 4.1 (Gaussian elimination, LU factorization) |
Oct
6 4.1-4.2 (LU factorization) HW 0 due |
|
2 |
Oct
9 4.3-4.5 (permutation matrices, PLU factorization) |
|
Oct
11 17.1-17.3 (positive definite matrices, Cholesky) |
Oct
13 5, 17.4 (banded LU, PLU, Cholesky) HW 1 due |
|
3 (Quiz week) |
Oct 16 8.1-8.2, 9.1-9.2 (matrix and vector norms) |
Oct
17 Quiz 1 (Canvas) |
Oct
18 9.3-9.4, 10.1 (matrix norms, condition number, perturbation theory) |
Oct
20 10.2-10.4 (perturbation theory) HW 2 due |
|
4
|
Oct
23 16.4, 15.1 (Gram-Schmidt, orthogonal matrices) |
|
Oct
25 15.1, 15.3, 16.3 (orthogonal matrices, Householder reflectors, full QR) |
Oct 27 16.3, 16.5, + (full QR, least squares setup) HW 3 due |
|
5 (Midterm week) |
Oct
30 16.2+ (least squares with QR) |
|
Nov
1 Review for Midterm |
Nov
2 MIDTERM 8-9:50pm A00: PETER 108 B00: PETER 108 |
Nov
3 23+ (the singular value decomposition, SVD) |
6 |
Nov
6 24.2, 24.4-24.5 (spectral norm, condition number, low-rank approximation) |
|
Nov
8 24.1, 24.3 (least squares with SVD, pseudoinverse) |
Nov 10 Veterans' Day NO CLASS HW 4 due |
|
7 (Quiz week) |
Nov 13 19.1 (eigenvalues; direct vs. indirect methods) |
Nov 14 Quiz 2 (Canvas) |
Nov
15 19.2, 19.4 (eigenvalues, diagonalization, similarity) |
Nov
17 20.1-20.2 (the power method) HW 5 due |
|
8 |
Nov
20 22.4-22.5 (Hessenberg form, QR iteration) |
|
Nov 22 23.3 (computing the SVD via eigenvalues) |
Nov
24 Thanksgiving Break NO CLASS |
|
9 (Quiz week) |
Nov 27 Catch-up HW 6 due |
Nov 28 Quiz 3 (Canvas) |
Nov
29 25.1+ (iterative methods) |
Dec
1 25.1 (Jacobi) |
|
10 |
Dec 4 25.2 (Gauss-Seidel) |
Dec 6 25.1-25.2 (complexity and convergence of Jacobi and Gauss-Seidel) |
|
Dec
8 Review for FINAL, which is on DEC 9 HW 7 due |
Prerequisites:
Lectures: Attending the in-person lectures and
watching the podcast / recording when in-person attendance is
not possible is a fundamental part of the
course. You are responsible for
material presented in the lectures whether
or not it is discussed in the textbook. You should
expect questions on the exams that will test your
understanding of concepts discussed in the lectures.
Discussion sections: Participation in
discussion sections is greatly encouraged. Make use of the
time that your TAs offer! Attend the discussions to see more
examples, work through problems, and talk to your TAs in a
small-group setting.
Homework: Homework assignments will be
posted on Canvas and will be due at 11:59pm on the indicated
due date (note Homework 0-5 and Homework 7 are due on Fridays,
while Homework 6, due to the Thanksgiving Break, is due on the
next Monday).
You must turn in your homework through Gradescope. A
PDF or picture is required to upload; if (and only if)
you have clean and neat handwriting, it is permitted to turn
in pictures/scans of homework done on paper. Assignments
should be in a single PDF file before being uploaded, or
as a picture for each question. It is allowed
and even encouraged to discuss homework
problems with your classmates and your instructor and TA, but
your final write up of your homework solutions must be your
own work. If you worked in a group, you must specify that
and write down all group members' names on the first page of
your homework.
Lowest score: There will be 8 homework
sets; the first one will only be graded for
completion. Only the 7 proportionally highest scores
will be counted towards your grade.
Midterm and Final Exams: Both the midterm and the final will be in-person; the midterm will take place on the date indicated, in the evening. The final will be administered on the date, and at the place and time indicated in the schedule of classes. The dates are listed in the calendar. There will be no makeup opportunities for either, except in the most serious of circumstances.
Quizzes: They will be held at the date and
time stated above.
Administrative Links: Here are two
links regarding UC San Diego policies on exams:
Regrade Policy:
Grading: Your cumulative average will be the best of the following two weighted averages:
Your course grade will be determined by your cumulative
average at the end of the quarter. Grading will not be curved.
You will need roughly 90% to get A- or above, roughly 80%
to get a B- or above, and roughly 60% to get a C- or above.
This is guaranteed, meaning that you will not get a
worse grade than specified above. However, you will not get a
pass (or P) unless you get a C- or above
score, so aim for at least 60%.
Etiquette
In addition, here are a few of my expectations for etiquette.