Variations and extensions of the Gaussian concentration inequality, Part I

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dc.contributor.author Fresen, Daniel J.
dc.date.accessioned 2023-09-12T10:36:29Z
dc.date.available 2023-09-12T10:36:29Z
dc.date.issued 2023
dc.description.abstract The classical Gaussian concentration inequality for Lipschitz functions is adapted to a setting where the classical assumptions (i.e. Lipschitz and Gaussian) are not met. The theory is more direct than much of the existing theory designed to handle related generalizations. An application is presented to linear combinations of heavy tailed random variables. en_US
dc.description.department Mathematics and Applied Mathematics en_US
dc.description.librarian hj2023 en_US
dc.description.uri https://www.tandfonline.com/loi/tqma20 en_US
dc.identifier.citation Daniel J. Fresen (2023) Variations and extensions of the Gaussian concentration inequality, Part I, Quaestiones Mathematicae, 46:7, 1367-1384, DOI: 10.2989/16073606.2022.2074908. en_US
dc.identifier.issn 1607-3606 (print)
dc.identifier.issn 1727-933X (online)
dc.identifier.other 10.2989/16073606.2022.2074908
dc.identifier.uri http://hdl.handle.net/2263/92274
dc.language.iso en en_US
dc.publisher Taylor and Francis en_US
dc.rights © 2022 NISC (Pty) Ltd. This is an electronic version of an article published in Quaestiones Mathematicae, vol. 46, no. 7, pp. 1367-1384, 2022. doi : 10.2989/16073606.2022.2074908. Quaestiones Mathematicae is available online at: https://www.tandfonline.com/loi/tqma20. en_US
dc.subject Gaussian concentration inequality en_US
dc.subject Heavy tailed random variables en_US
dc.title Variations and extensions of the Gaussian concentration inequality, Part I en_US
dc.type Postprint Article en_US


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