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Bibliographic Details
Main Author: Gordin, Miriam
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.09607
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author Gordin, Miriam
author_facet Gordin, Miriam
contents We present vector-valued concentration inequalities for the biased measure on the discrete hypercube with an optimal dependence on the bias parameter and the Rademacher type of the target Banach space. These results allow us to obtain novel vector-valued concentration inequalities for the measure given by a product of Poisson distributions. Furthermore, we obtain lower bounds on the average distortion with respect to the biased measure of embeddings of the hypercube into Banach spaces of nontrivial type which imply average non-embeddability.
format Preprint
id arxiv_https___arxiv_org_abs_2410_09607
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Vector-valued concentration inequalities on the biased discrete cube
Gordin, Miriam
Probability
Functional Analysis
60E15 (Primary) 46B85, 46B09, 30L15
We present vector-valued concentration inequalities for the biased measure on the discrete hypercube with an optimal dependence on the bias parameter and the Rademacher type of the target Banach space. These results allow us to obtain novel vector-valued concentration inequalities for the measure given by a product of Poisson distributions. Furthermore, we obtain lower bounds on the average distortion with respect to the biased measure of embeddings of the hypercube into Banach spaces of nontrivial type which imply average non-embeddability.
title Vector-valued concentration inequalities on the biased discrete cube
topic Probability
Functional Analysis
60E15 (Primary) 46B85, 46B09, 30L15
url https://arxiv.org/abs/2410.09607