Evidence map›Paper›PMID 36691583›Full record

ArticleStatistics and computing2023

On randomized sketching algorithms and the Tracy-Widom law.

Daniel Ahfock, William J Astle, Sylvia Richardson

Abstract read
In one paragraph

Article in Statistics and computing, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Daniel AhfockMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.ORCID 0000-0002-8075-6443
William J AstleMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Sylvia RichardsonMRC Biostatistics Unit, University of Cambridge, Cambridge, UK.

Funding

Medical Research Council MC_PC_17228Medical Research Council MC_UU_00002/10
6 · The paper itself

Abstract

There is an increasing body of work exploring the integration of random projection into algorithms for numerical linear algebra. The primary motivation is to reduce the overall computational cost of processing large datasets. A suitably chosen random projection can be used to embed the original dataset in a lower-dimensional space such that key properties of the original dataset are retained. These algorithms are often referred to as sketching algorithms, as the projected dataset can be used as a compressed representation of the full dataset. We show that random matrix theory, in particular the Tracy-Widom law, is useful for describing the operating characteristics of sketching algorithms in the tall-data regime when the sample size Supplementary Information: The online version contains supplementary material available at 10.1007/s11222-022-10148-5.

Indexed as

Random matrix theoryRandom projectionSketching

Identifiers

PMID36691583
PMCPMC9852177

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.