UAI 2021poster1 citations
Path-BN: Towards effective batch normalization in the Path Space for ReLU networks
Xufang Luo, Qi Meng, Wei Chen, Yunhong Wang, Tie-Yan Liu
Abstract
Neural networks with ReLU activation functions (abbrev. ReLU Networks), have demonstrated their success in many applications. Recently, researchers noticed that ReLU networks are positively scale-invariant (PSI) while the weights are not. This mismatch may lead to undesirable behaviors in the optimization process. Hence, some new algorithms that conduct optimization directly in the
BibTeX
@InProceedings{pmlr-v161-luo21b,
title = {Path-BN: Towards effective batch normalization in the Path Space for ReLU networks},
author = {Luo, Xufang and Meng, Qi and Chen, Wei and Wang, Yunhong and Liu, Tie-Yan},
booktitle = {Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence},
pages = {834--843},
year = {2021},
editor = {de Campos, Cassio and Maathuis, Marloes H.},
volume = {161},
series = {Proceedings of Machine Learning Research},
month = {27--30 Jul},
publisher = {PMLR},
pdf = {https://proceedings.mlr.press/v161/luo21b/luo21b.pdf},
url = {https://proceedings.mlr.press/v161/luo21b.html},
abstract = {Neural networks with ReLU activation functions (abbrev. ReLU Networks), have demonstrated their success in many applications. Recently, researchers noticed that ReLU networks are positively scale-invariant (PSI) while the weights are not. This mismatch may lead to undesirable behaviors in the optimization process. Hence, some new algorithms that conduct optimization directly in the