Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions
Abstract
We study the dynamics of optimization and the generalization properties of one-hidden layer neural networks with quadratic activation function in the overparametrized regime where the layer width m is larger than the input dimension d.
Cite
Text
Mannelli et al. "Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions." Neural Information Processing Systems, 2020.Markdown
[Mannelli et al. "Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions." Neural Information Processing Systems, 2020.](https://mlanthology.org/neurips/2020/mannelli2020neurips-optimization/)BibTeX
@inproceedings{mannelli2020neurips-optimization,
title = {{Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions}},
author = {Mannelli, Stefano Sarao and Vanden-Eijnden, Eric and Zdeborová, Lenka},
booktitle = {Neural Information Processing Systems},
year = {2020},
url = {https://mlanthology.org/neurips/2020/mannelli2020neurips-optimization/}
}