N. Halko, P. G. Martinsson, J. A. Tropp: Finding Structure with Randomness:
Probabilistic Algorithms for Constructing Approximate Matrix Decompositions,
SIAM REVIEW, Vol. 53, No. 2, (2011)217–288
Matrix Analysis for Scientists and Engineers
by Alan J. Laub, SIAM, Philadelphia
Alan J. Laub, Matrix Analysis for Scientists and Engineers, SIAM, Philadelphia, 2005
Applied Algebra
| Language of instruction | angličtina, čeština |
|---|---|
| Code | 470-4201 |
| Abbreviation | AA |
| Course title | Applied Algebra |
| Coordinating department | Department of Applied Mathematics |
| Course coordinator | prof. RNDr. Zdeněk Dostál, DSc. |
Summary
Vector space, orthogonality, special bases (hierarchical, Fourier, wavelets), linear mapping, bilinear an quadratic forms, matrix decompositions (spectral, Schur, SVD), Markov's precesses, Page Rank vector, linear algebra of huge matrices, low rank approximation of large matrices, quadratic programming, SVM, tensors. Applications in information technology.
Literature
Advised literature
Tamara G. Kolda, Brett W. Bader. Tensor Decompositions and Applications, SIAM Review, Vol. 51, No. 3, (2009)455–500
Carl D. Meyer, Matrix analysis and applied linear algebra, SIAM, Philadelphia, 2000
Dianne P. O'Leary, Scientific Computing with Case Studies, SIAM, Philadelphia 2009
Carl D. Meyer, Matrix analysis and applied linear algebra, SIAM, Philadelphia, 2000
Dianne P. O'Leary, Scientific Computing with Case Studies, SIAM, Philadelphia 2009