Block 1 - Low rank data algorithms
This block consists of five lectures and one homework set (see homework page).
There are also office hours where you can ask questions about the homework and other things in the course.
Between lectures you should work on your own with the material shown in the asynchronous learning sections:
- Video quizzes. These are mandatory.
- Optional, but recommended, video material to watch for deeper understanding.
- First homework set. Work on this during the whole block. The deadline is 5/2.
The reading material referenced is:
- EJ0 = Background material on linear algebra
Download Background material on linear algebra, by Elias Jarlebring
- EJ1 = Lecture notes on low-rank data algorithms Download Lecture notes on low-rank data algorithms, by Elias Jarlebring
- PGM = Lecture notes on fast algorithms for big data Download Lecture notes on fast algorithms for big data, by Per-Gunnar Martinsson
- GvL = Extract about SVD, Download Extract about SVD, from the book Matrix Computations, by Gene Golub and Charles van Loan
Recommended exercises are in the files:
- AL19 = Active Learning 2019
Download Active Learning 2019
- AL20 = Active Learning 2020
Download Active Learning 2020
OBS! The schedule below is preliminary. Minor changes may be made.
Date | Activities | Reading and recommended exercises |
Asynchronous learning 1
|
Reading:
|
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14/1 |
Lecture 1
|
Reading:
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Asynchronous learning 2
|
Reading:
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|
17/1 |
Lecture 2
|
Reading:
|
Asynchronous learning 3
|
Reading:
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|
21/1 |
Office hours |
|
22/1 |
Lecture 3
|
Reading:
|
Asynchronous learning 4
|
Reading:
|
|
24/1 |
Lecture 4
|
Reading:
Recommended exercises:
|
Asynchronous learning 5
|
Reading:
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28/1 | Lecture 5
|
Reading:
Recommended exercises:
|
5/2 | Deadline Homework 1 |
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