Proofs and additional experiments on Second order techniques for learning time-series with structural breaks
Machine Learning
2021-02-17 v2 Machine Learning
Abstract
We provide complete proofs of the lemmas about the properties of the regularized loss function that is used in the second order techniques for learning time-series with structural breaks in Osogami (2021). In addition, we show experimental results that support the validity of the techniques.
Cite
@article{arxiv.2012.08037,
title = {Proofs and additional experiments on Second order techniques for learning time-series with structural breaks},
author = {Takayuki Osogami},
journal= {arXiv preprint arXiv:2012.08037},
year = {2021}
}
Comments
10 pages, 9 figures