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Autori principali: Elperin, Ariel, Kontorovich, Aryeh
Natura: Preprint
Pubblicazione: 2025
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Accesso online:https://arxiv.org/abs/2506.16930
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author Elperin, Ariel
Kontorovich, Aryeh
author_facet Elperin, Ariel
Kontorovich, Aryeh
contents We closely examine a notion of average smoothness recently introduced by Ashlagi et al. (JMLR, 2024). The latter defined a {\em weak} and {\em strong} average-Lipschitz seminorm for real-valued functions on general metric spaces. Specializing to the standard metric on the real line, we compare these notions to bounded variation (BV) and discover that the weak notion is strictly weaker than BV while the strong notion strictly stronger. Along the way, we discover that the weak average smooth class is also considerably larger in a certain combinatorial sense, made precise by the fat-shattering dimension.
format Preprint
id arxiv_https___arxiv_org_abs_2506_16930
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Bounded variation separates weak and strong average Lipschitz
Elperin, Ariel
Kontorovich, Aryeh
Functional Analysis
We closely examine a notion of average smoothness recently introduced by Ashlagi et al. (JMLR, 2024). The latter defined a {\em weak} and {\em strong} average-Lipschitz seminorm for real-valued functions on general metric spaces. Specializing to the standard metric on the real line, we compare these notions to bounded variation (BV) and discover that the weak notion is strictly weaker than BV while the strong notion strictly stronger. Along the way, we discover that the weak average smooth class is also considerably larger in a certain combinatorial sense, made precise by the fat-shattering dimension.
title Bounded variation separates weak and strong average Lipschitz
topic Functional Analysis
url https://arxiv.org/abs/2506.16930