English

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 rr-order (an)-isotropic total variation semi-norms TVrTV^r, rR+r\in \mathbb{R}^+, 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 rr, 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}
}