Disclaimer: This is the website of lecture A. Lecture B runs in parallel and is taught by Ioana Dumitriu. Before continuing on this website, please make sure you are actually enrolled in lecture A.
| Name | Role | Section | Office hour | |
|---|---|---|---|---|
| Caroline Moosmüller | Instructor | cmoosmueller (at) ucsd (dot) edu | A00 | MW 10-11 am and by appointment |
| Hangran Zhang | TA | haz355 (at) ucsd (dot) edu | A01, A02 | Tu 4-6 pm |
| Lin Zheng | TA | liz176 (at) ucsd (dot) edu | A03, A04 | Tu 1:30 - 3:30 pm |
| Noah Applegate | Study group leader | napplega (at) ucsd (dot) edu | Study group |
Lectures, discussion sections and office hours will be held synchronously via zoom (links available on Canvas). Recordings of all lectures and discussion sections will be made available on Canvas.
Note that all discussion sections cover the same material, so it is enough to join one of the discussion sections.
You may attend the office hours of any and all instructors, regardless of discussion section enrollment.
Attendance is not mandatory, but highly recommended!
| Meeting type | Instructor | Date | Time | Place |
|---|---|---|---|---|
| Lecture A00 | Caroline Moosmüller | MWF | 9-9:50 am | Zoom LTI PRO tab in Canvas |
| Discussion A01 | Hangran Zhang | Tu | 8-8:50 am | Zoom LTI PRO tab in Canvas |
| Discussion A02 | Hangran Zhang | Tu | 9-9:50 am | Zoom LTI PRO tab in Canvas |
| Discussion A03 | Lin Zheng | Tu | 10-10:50 am | Zoom LTI PRO tab in Canvas |
| Discussion A04 | Lin Zheng | Tu | 11-11:50 am | Zoom LTI PRO tab in Canvas |
| Study group | Noah Applegate | Th | 4-5:20 pm | Canvas |
| Office hour | Caroline Moosmüller | MW | 10-11 am | Zoom LTI PRO tab in Canvas |
| Office hour | Lin Zheng | Tu | 1:30-3:30 pm | Zoom LTI PRO tab in Canvas |
| Office hour | Hangran Zhang | Tu | 4-6 pm | Zoom LTI PRO tab in Canvas |
Mar 12: Final review
Mar 10: Chapter 8.1-8.3: iterative methods, Gauss-Seidel method
Mar 8: Chapter 8.1-8.3: iterative methods, Jacobi method
Mar 5: QR iteration flop count Intro to MATH 170B
Mar 3: Chapter 5.5: Upper Hessenberg matrices, QR iteration Review for quiz 3
Mar 1: QR iteration intro
Feb 26: Chapter 5.3: Power method example, Chapter 5.4: Similarity transforms
Feb 24: Chapter 5.3: Power method
Feb 22: Chapter 5.2: More on eigenvalues/vectors
Feb 19: Chapter 4.3: pseudo inverse, Chapter 5.1: Eigenvalues intro
Feb 17: Chapter 4.3: Least squares with SVD Quiz 2 review
Feb 12: Chapter 4.2: more SVD
Feb 10: Chapter 2.2/3: condition number, perturbations and Chapter 4.1: SVD
Feb 8: Chapter 2.2/3: condition number, perturbations
Feb 5: Chapter 3.2: proof of full QR, Chapter 3.4: reduced QR
Feb 3: Review for midterm
Feb 1: Chapter 3.2: Projectors, reflectors, proof of QR
Jan 29: Chapter 3.1/2/3: Solve least squares, projectors
Jan 27: Chapter 3.1/2/3: Intro least squares, orthogonal matrices, QR
Jan 25: Chapter 2.1: Norms
Jan 22: Chapter 1.4: Cholesky decomposition, Chapter 2.1: Norms
Jan 20:
Chapter 1.4: Cholesky decomposition
Office hour: review for quiz 1
Jan 15: Chapter 1.7: LU decomposition, Chapter 1.8: Gauss elimination with pivoting
Jan 13:
Chapter 1.7: Gauss elimination (continuation)
Code (Gauss_solve.m)
Jan 11:
Chapter 1.3: Lower triangular system flop count, Chapter 1.7: Gauss elimination
Code (lowertriagsolve.m)
Jan 8: Chapter 1.2: Finish ODE example, Chapter 1.3: triangular systems
Jan 6: Chapter 1.1: Big-Oh notation, Chapter 1.2: linear systems motivation
Jan 4: Chapter 1.1: Matrix multiplications
Week 10: Discussion section will go over some of the problems of the sample final. To prepare, try to solve the problems on the sample final, see homework.
Week 9: pdf with problems
Week 8: pdf with problems
Week 7: pdf with problems
Week 6: pdf with problems
Week 5: Discussion section will go over some of the problems of the sample midterm. To prepare, try to solve the problems on the sample midterm, see homework.
Week 4: pdf with problems
Week 3: pdf with problems
Week 2: pdf with problems
Week 1: Discussion sections will go over basic MATLAB programming. To prepare for discussions, write a short MATLAB program that computes the inner product using a for-loop.