nla2022_masters
nla2022_masters copied to clipboard
Published
20 hours ago •
amkatrutsa
amkatrutsa
NLA course in AI masters
Numerical Linear Algebra in AI Masters, Fall 2022
| Date | Lectures | Practice sessions | Home assignments |
|---|---|---|---|
| 15.09.2022 | General info about the course. Floating point numbers. Vector norms | Review and main policies | HW1 (Deadline: October, 4, 23:59 MSK) |
| 22.09.2022 | Matrix norms and unitary matrices | Seminar 2 | |
| 29.09.2022 | Seminar 3 Seminar 4 |
HW2 (Deadline: October, 11, 23:59 MSK) |
|
| 06.10.2022 | Matrix rank and low-rank approximation. SVD. Linear systems |
||
| 13. 10.2022 | Matrix multiplication and memory hierarchy. | Seminar 5 | HW3 (Deadline: October, 25, 23:59 MSK) |
| 20.10.2022 | Seminar 6 Seminar 7 |
||
| 27.10.2022 | QR decomposition and how to compute it. Eigenvalues and eigenvectors. Schur decomposition. QR algorithm. SVD and how we compute it. |
||
| 03.11.2022 | Seminars 8 and 9 | ||
| 10.11.2022 | Sparse matrices and direct methods for large sparse linear systems. Spectral partitioning and Fiedler vector Intro to iterative methods |
||
| 17.11.2022 | Great iterative methods | Seminar 10 | |
| 24.11.2022 | Seminar 11 Seminar 12 |
HW4 (Deadline: December, 4, 23:59 MSK) |
|
| 01.12.2022 | Iterative methods and preconditioners | Seminar 13 | |
| 08.12.2022 | Iterative methods for partial eigenvalue problem | Seminar 14 | HW5 (Deadline: December, 15, 23:59 MSK) |
| 16.12.2022 | Structured matrices, convolutions, FFT, Toeplitz matrices Matrix functions and randomized methods in NLA |
amkatrutsa