Real order total variation with applications to the loss functions in learning schemes
Analysis of PDEs
2022-04-12 v1 Machine Learning
Abstract
Loss function are an essential part in modern data-driven approach, such as bi-level training scheme and machine learnings. In this paper we propose a loss function consisting of a -order (an)-isotropic total variation semi-norms , , defined via the Riemann-Liouville (R-L) fractional derivative. We focus on studying key theoretical properties, such as the lower semi-continuity and compactness with respect to both the function and the order of derivative , of such loss functions.
Keywords
Cite
@article{arxiv.2204.04582,
title = {Real order total variation with applications to the loss functions in learning schemes},
author = {Pan Liu and Xin Yang Lu and Kunlun He},
journal= {arXiv preprint arXiv:2204.04582},
year = {2022}
}