Numerical linear algebra course, @SkolTech, Term 2, 2018

https://nla.skoltech.ru,

This repository contains lectures and homeworks for Numerical linear algebra course. It will be updated as the class progresses.

| Week | Lecture notebooks | Supplementary materials | Homework | Tests | |:------:|:----------|:----------|:----------|-------| |1| General info [GitHub, Nbviewer] <br> Lecture 1. Floating-point arithmetic, vector norms [GitHub, Nbviewer] <br> Lecture 2. Matrix norms and unitary matrices [GitHub, Nbviewer]| Python intro | Requirements <br> Problem set 1 <br> Deadline: 11/11/18 (23:59)| Pre-term test | |2| Lecture 3. Matvecs and matmuls, memory hierarchy, Strassen algorithm [GitHub, Nbviewer] <br> Lecture 4. Matrix rank, low-rank approximation, SVD [GitHub, Nbviewer] <br> Lecture 5. Linear systems [GitHub, Nbviewer]| Notes on matrix calculus [GitHub, Nbviewer] | | | |3| Lecture 6. Eigenvalues and eigenvectors [GitHub, Nbviewer] <br> Lecture 7. Matrix decompositions and how we compute them [GitHub, Nbviewer] <br> Lecture 8. Symmetric eigenvalue problem and SVD [GitHub, Nbviewer] | Examples of projects | Problem set 2 <br> Deadline: 27/11/18 (00:02) | |4| Lecture 9. From dense to sparse linear algebra [GitHub, Nbviewer] <br> Lecture 10. Sparse direct solvers [GitHub, Nbviewer] <br> Lecture 11. Intro to iterative methods [GitHub, Nbviewer] | | | |5| Lecture 12. Great iterative methods [GitHub, Nbviewer] <br> Lecture 13. Iterative methods and preconditioners [GitHub, Nbviewer] | | Problem set 3 <br> Deadline: 05/12/18 (23:59) | Exam questions | |6| Lecture 14. Iterative methods for large scale eigenvalue problems [GitHub, Nbviewer] <br> Lecture 15. Structured matrices, FFT, convolutions, Toeplitz matrices [GitHub, Nbviewer] <br> Lecture 16. Matrix functions and matrix equations [GitHub, Nbviewer] <br> Lecture 17. Tensors and tensor decompositions [GitHub, Nbviewer] | | | NLA basics |