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] Lecture 1. Floating point arithmetic, vector norms [GitHub] Lecture 2. Matrix norms and unitary matrices [GitHub] Lecture 3. Matvecs and matmuls, memory hierarchy, Strassen algorithm [GitHub] |
Brief Python intro JAX intro |
Home assignment 1 Deadline: November, 8, 23:59 MSK |
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| 2 | Lecture 4. Matrix rank, low-rank approximation, SVD [GitHub] Lecture 5. Linear systems [Github] Lecture 6. Eigenvalues and eigenvectors [GitHub] |
PyTorch intro | ||
| 3 | Lecture 7. Matrix decompositions and how we compute them [GitHub] Lecture 8. Symmetric eigenvalue problem and SVD [GitHub] Lecture 9. From dense to sparse linear algebra [GitHub] |
Home assignment 2 Deadline: November, 23, 23:59 MSK |
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| 4 | Lecture 10. Sparse direct solvers [GitHub] Lecture 11. Intro to iterative methods [GitHub] Lecture 12. Great iterative methods [GitHub] |
CG convergence | Exam questions Theoretical minimum questions |
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| 5 | Lecture 13. Iterative methods and preconditioners [GitHub] Lecture 14. Structured matrices, FFT, convolutions, Toeplitz matrices [GitHub] Lecture 15. Matrix functions and matrix equations [GitHub] |
Home assignment 3 Deadline: December, 4, 23:59 MSK |
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| 6 | Lecture 16. Large scale eigenvalue problem [GitHub] Lecture 17. Tensors and tensor decompositions [GitHub] |