Randomized Linear Algebra Algorithm: Difference between revisions
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* ([[2016_RandNLARandomizedNumericalLinea|Drineas & Mahoney, 2016]]) ⇒ [[Petros Drineas]], and [[Michael W. Mahoney]]. ([[2016]]). “RandNLA: Randomized Numerical Linear Algebra.” In: [[Communications of the ACM Journal]], 59(6). [http://dx.doi.org/10.1145/2842602 doi:10.1145/2842602] | * ([[2016_RandNLARandomizedNumericalLinea|Drineas & Mahoney, 2016]]) ⇒ [[Petros Drineas]], and [[Michael W. Mahoney]]. ([[2016]]). “RandNLA: Randomized Numerical Linear Algebra.” In: [[Communications of the ACM Journal]], 59(6). [http://dx.doi.org/10.1145/2842602 doi:10.1145/2842602] | ||
** QUOTE: Particularly remarkable is the use of [[randomized algorithm|randomization]] — typically assumed to be a property of the [[input data]] due to, for example, [[noise]] in the [[data generation mechanism]]s — as an [[algorithmic resource|algorithmic]] or [[computational resource]] for the [[algorithm development|development]] of improved [[algorithms for fundamental matrix problem]]s such as [[matrix multiplication]], [[least-squares (LS) approximation]], [[low-rank matrix approximation]], and [[Laplacian-based linear equation solver]]s. </s> <P> | ** QUOTE: Particularly remarkable is the use of [[randomized algorithm|randomization]] — typically assumed to be a property of the [[input data]] due to, for example, [[noise]] in the [[data generation mechanism]]s — as an [[algorithmic resource|algorithmic]] or [[computational resource]] for the [[algorithm development|development]] of improved [[algorithms for fundamental matrix problem]]s such as [[matrix multiplication]], [[least-squares (LS) approximation]], [[low-rank matrix approximation]], and [[Laplacian-based linear equation solver]]s. </s> <P> [[Randomized Linear Algebra Algorithm|Randomized Numerical Linear Algebra (RandNLA)]] is an interdisciplinary research area that exploits [[randomized algorithm|randomization]] as a [[computational resource]] to develop improved [[matrix algorithm|algorithm]]s for [[large-scale linear algebra]] problems.32 </s> | ||
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Latest revision as of 01:51, 27 February 2024
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.