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High Dimensional Probability VIOn Some Gaussian Concentration Inequality for Non-Lipschitz Functions

High Dimensional Probability VI: On Some Gaussian Concentration Inequality for Non-Lipschitz... [A concentration inequality for functions of a pair of Gaussian random vectors is established. Instead of the usual Lipschitz condition some boundedness of second-order derivatives is assumed. This result can be viewed as an extension of a well-known tail estimate for Gaussian random bi-linear forms to the non-linear case.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

High Dimensional Probability VIOn Some Gaussian Concentration Inequality for Non-Lipschitz Functions

Part of the Progress in Probability Book Series (volume 66)
Editors: Houdré, Christian; Mason, David M.; Rosiński, Jan; Wellner, Jon A.
Wolff, Paweł
High Dimensional Probability VI — Apr 1, 2013
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References (5)

Publisher
Springer Basel
Copyright
© Springer Basel 2013
ISBN
978-3-0348-0489-9
Pages
103 –110
DOI
10.1007/978-3-0348-0490-5_8
Publisher site
See Chapter on Publisher Site

Abstract

[A concentration inequality for functions of a pair of Gaussian random vectors is established. Instead of the usual Lipschitz condition some boundedness of second-order derivatives is assumed. This result can be viewed as an extension of a well-known tail estimate for Gaussian random bi-linear forms to the non-linear case.]

Published: Apr 1, 2013

Keywords: Concentration inequality; Gaussian measure; Gaussian chaos

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