Sampling based succinct matrix approximation

Rong Liu and Yong Shi

Statistics & Probability Letters, 2008, vol. 78, issue 9, 1138-1147

Abstract: This work furnishes a sharper bound of exponential form to the L2 norm of an arbitrary shaped random matrix. On the basis of this bound, a non-uniform sampling method is developed for approximating a matrix with a sparse binary one. Both time and storage loads of matrix computations can hereby be relieved with limited loss of information. The sampling and quantizing approaches are naturally combined together in the approximation. Furthermore, this method is pass-efficient because the whole process can be completed within one pass over the input matrix. The sampling method demonstrated an impressive capability of providing succinct and tight approximations (data reduction) for input matrices in the experimental evaluation on a large data set.

Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(07)00385-9
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:78:y:2008:i:9:p:1138-1147

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().