NeurIPS 2017poster1601 citations
Exploring Generalization in Deep Learning
Behnam Neyshabur, Srinadh Bhojanapalli, David Mcallester, Nati Srebro
Abstract
With a goal of understanding what drives generalization in deep networks, we consider several recently suggested explanations, including norm-based control, sharpness and robustness. We study how these measures can ensure generalization, highlighting the importance of scale normalization, and making a connection between sharpness and PAC-Bayes theory. We then investigate how well the measures explain different observed phenomena.
BibTeX
@inproceedings{NIPS2017_10ce03a1,
author = {Neyshabur, Behnam and Bhojanapalli, Srinadh and Mcallester, David and Srebro, Nati},
booktitle = {Advances in Neural Information Processing Systems},
editor = {I. Guyon and U. Von Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Exploring Generalization in Deep Learning},
url = {https://proceedings.neurips.cc/paper_files/paper/2017/file/10ce03a1ed01077e3e289f3e53c72813-Paper.pdf},
volume = {30},
year = {2017}
}