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On Euclidean random matrices in high dimension

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	On Euclidean random matrices in high dimension
2.	Creator	Author's name, affiliation, country	Charles Bordenave; Université de Toulouse & CNRS; France
3.	Subject	Discipline(s)
3.	Subject	Keyword(s)	Euclidean random matrices, Marcenko-Pastur distribution, Log-concave distribution.
3.	Subject	Subject classification	60B20 ; 15A18.
4.	Description	Abstract	In this note, we study the n x n random Euclidean matrix whose entry (i,j) is equal to f (|| Xi - Xj ||) for some function f and the Xi's are i.i.d. isotropic vectors in Rp. In the regime where n and p both grow to infinity and are proportional, we give some sufficient conditions for the empirical distribution of the eigenvalues to converge weakly. We illustrate our result on log-concave random vectors.
5.	Publisher	Organizing agency, location
6.	Contributor	Sponsor(s)
7.	Date	(YYYY-MM-DD)	2013-04-05
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	http://ecp.ejpecp.org/article/view/2340
10.	Identifier	Digital Object Identifier	10.1214/ECP.v18-2340
11.	Source	Journal/conference title; vol., no. (year)	Electronic Communications in Probability; Vol 18
12.	Language	English=en	en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
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