Randomized Linear Algebra Algorithm: Difference between revisions
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Revision as of 21:21, 26 May 2016
A Randomized Linear Algebra Algorithm is a linear algebra algorithm that is a randomized numerical algorithm.
References
2016
- (Drineas & Mahoney, 2016) ⇒ Petros Drineas, and Michael W. Mahoney. (2016). "RandNLA: Randomized Numerical Linear Algebra." In: Communications of the ACM Journal, 59(6). doi:10.1145/2842602
- QUOTE: Particularly remarkable is the use of randomization — typically assumed to be a property of the input data due to, for example, noise in the data generation mechanisms — as an algorithmic or computational resource for the development of improved algorithms for fundamental matrix problems such as matrix multiplication, least-squares (LS) approximation, low-rank matrix approximation, and Laplacian-based linear equation solvers.
Randomized Numerical Linear Algebra (RandNLA) is an interdisciplinary research area that exploits randomization as a computational resource to develop improved algorithms for large-scale linear algebra problems.32
- QUOTE: Particularly remarkable is the use of randomization — typically assumed to be a property of the input data due to, for example, noise in the data generation mechanisms — as an algorithmic or computational resource for the development of improved algorithms for fundamental matrix problems such as matrix multiplication, least-squares (LS) approximation, low-rank matrix approximation, and Laplacian-based linear equation solvers.