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Randomized methods for matrix computations

Abstract:

The purpose of this text is to provide an accessible introduction to a set of recently developed algorithms for factorizing matrices. These new algorithms attain high practical speed by reducing the dimensionality of intermediate computations using randomized projections. The algorithms are particularly powerful for computing low-rank approximations to very large matrices, but they can also be used to accelerate algorithms for computing full factorizations of matrices. A key competitive advan...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted Manuscript

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Publisher copy:
10.1090/pcms/025

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Institution:
University of Oxford
Division:
MPLS Division
Department:
Mathematical Institute
Oxford college:
Christ Church
ORCID:
0000-0002-1048-5270
Publisher:
American Mathematical Society Publisher's website
Volume:
25
Pages:
187-230
Series:
IAS/Park City Mathematics Series
Host title:
Mathematics of Data
Publication date:
2019-03-19
Acceptance date:
2018-06-05
DOI:
Pubs id:
pubs:691621
URN:
uri:a654f823-c927-4fb8-8fae-e557ef2dee3d
UUID:
uuid:a654f823-c927-4fb8-8fae-e557ef2dee3d
Local pid:
pubs:691621
ISBN:
978-1-4704-3575-2
Keywords:

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