Date | Topic | Reading | Assignment |
---|---|---|---|
4/2 | Syllabus and Mathematics review | Lecture note Sec.1.1-1.3 of Solomon |
... |
4/4 | Approximation and error analysis | Lecture,
Handout #1 Sec.2.2 of Solomon |
... |
4/9 | Computer arithmetic | Lecture,
Handout #2,
Extra |
... |
4/11 | Intro to HPC (BLAS) | Lecture | Homework 1 |
4/16 | Vector and matrix norms | Handout #3, Extra | ... |
4/18 | Frequently used matrix decomposition 1/2 | Handout #4 | Homework 2 |
4/23 | Frequently used matrix decomposition 2/2 | Extra | ... |
4/25 | Iterative subspace methods for LS 1/2 | Handout #5, Lecture | ... |
4/30 | Iterative subspace methods for LS 2/2 | Extra | ... |
5/2 | Iterative subspace methods for EP 1/2 | Handout #6 | Homework 3 |
5/7 | Iterative subspace methods for EP 2/2 | ... | ... |
5/9 | Spectral clustering | Lecture | code |
5/14 | Gradient descent algorithms | Lecture | testSD.m,
testCG.m test data 1, test data 2 |
5/16 | Midterm Exam | Handouts #1-#6 | Homework #1-#3 |
5/21 | Randomized algorithms 1/2 | Lecture | lsbysampling.m,
lsbyrandprecond.m lsbygd.m, lsbysgd.m |
5/23 | Randomized algorithms 2/2 | Lecture | randsvd.m, randsvd2.m, randcur.m |
Extra office hours | 5/24, Friday, 9-10 5/28, Tuesday, 10-11 |
... | |
5/28 | PCA, revisted | Lecture | pca4ldc.m,
pca4dr.m data2D.mat |
5/30 | Fast algorithms 1/2 | Handout | ... |
5/31 | Extra office hour: 5:30 - 6:30 | ... | ... |
6/4 | Extended office hour: 8:30 - 10:30 | ... | ... |
6/4 | Fast algorithms 2/2 | ... | ... |
6/5 | Extended office hour: 4:00 - 6:30 | ... | ... |
6/6 | instruction ends No lecture, office hours from 4:30-6:00 |
... | Final project list Report guideline |
6/7 | Final project report due 3:00pm | no extension! | ... |