Stochastic Sample Approximations of (Local) Moduli of Continuity

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Nazarov, Rodion, Gehret, Allen, Shorten, Robert, Marecek, Jakub
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866911163236745216
author Nazarov, Rodion
Gehret, Allen
Shorten, Robert
Marecek, Jakub
author_facet Nazarov, Rodion
Gehret, Allen
Shorten, Robert
Marecek, Jakub
contents Modulus of local continuity is used to evaluate the robustness of neural networks and fairness of their repeated uses in closed-loop models. Here, we revisit a connection between generalized derivatives and moduli of local continuity, and present a non-uniform stochastic sample approximation for moduli of local continuity. This is of importance in studying robustness of neural networks and fairness of their repeated uses.
format Preprint
id arxiv_https___arxiv_org_abs_2509_15368
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stochastic Sample Approximations of (Local) Moduli of Continuity
Nazarov, Rodion
Gehret, Allen
Shorten, Robert
Marecek, Jakub
Machine Learning
Modulus of local continuity is used to evaluate the robustness of neural networks and fairness of their repeated uses in closed-loop models. Here, we revisit a connection between generalized derivatives and moduli of local continuity, and present a non-uniform stochastic sample approximation for moduli of local continuity. This is of importance in studying robustness of neural networks and fairness of their repeated uses.
title Stochastic Sample Approximations of (Local) Moduli of Continuity
topic Machine Learning
url https://arxiv.org/abs/2509.15368