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This course presents numerical methods for the solution of mathematical problems such as systems of linear and non-linear equations, functions approximation, integration and differentiation, and diffe
This course is concerned with randomized algorithms that have been developed during the last decade to solve large-scale linear algebra problems from, for example, scientific computing and statistica
Veuillez noter qu'il ne s'agit pas d'une liste complète des publications de cette personne. Elle inclut uniquement les travaux sémantiquement pertinents. Pour une liste complète, veuillez consulter Infoscience.
Toeplitz matrices are abundant in computational mathematics, and there is a rich literature on the development of fast and superfast algorithms for solving linear systems involving such matrices. Any Toeplitz matrix can be transformed into a matrix with of ...
The randomized singular value decomposition (SVD) has become a popular approach to computing cheap, yet accurate, low-rank approximations to matrices due to its efficiency and strong theoretical guarantees. Recent work by Boullé and Townsend [Found. Comput ...
Society for Industrial & Applied Mathematics (SIAM)2025
