Corpus ID: 222133914

# Smaller generalization error derived for deep compared to shallow residual neural networks

@article{Kammonen2020SmallerGE,
title={Smaller generalization error derived for deep compared to shallow residual neural networks},
author={Aku Kammonen and Jonas Kiessling and P. Plech{\'a}{\vc} and M. Sandberg and A. Szepessy and R. Tempone},
journal={ArXiv},
year={2020},
volume={abs/2010.01887}
}
Estimates of the generalization error are proved for a residual neural network with $L$ random Fourier features layers $\bar z_{\ell+1}=\bar z_\ell + \text{Re}\sum_{k=1}^K\bar b_{\ell k}e^{{\rm i}\omega_{\ell k}\bar z_\ell}+ \text{Re}\sum_{k=1}^K\bar c_{\ell k}e^{{\rm i}\omega'_{\ell k}\cdot x}$. An optimal distribution for the frequencies $(\omega_{\ell k},\omega'_{\ell k})$ of the random Fourier features $e^{{\rm i}\omega_{\ell k}\bar z_\ell}$ and $e^{{\rm i}\omega'_{\ell k}\cdot x}$ is… Expand

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