NeurIPS 2019poster941 citations
Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers
Zeyuan Allen-Zhu, Yuanzhi Li, Yingyu Liang
Abstract
The fundamental learning theory behind neural networks remains largely open. What classes of functions can neural networks actually learn? Why doesn't the trained network overfit when it is overparameterized?
BibTeX
@inproceedings{NEURIPS2019_62dad6e2,
author = {Allen-Zhu, Zeyuan and Li, Yuanzhi and Liang, Yingyu},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers},
url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/62dad6e273d32235ae02b7d321578ee8-Paper.pdf},
volume = {32},
year = {2019}
}