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BN-invariant sharpness regularizes the training model to better
  generalization

BN-invariant sharpness regularizes the training model to better generalization

8 January 2021
Mingyang Yi
Huishuai Zhang
Wei Chen
Zhi-Ming Ma
Tie-Yan Liu
ArXivPDFHTML

Papers citing "BN-invariant sharpness regularizes the training model to better generalization"

4 / 4 papers shown
Title
Understanding the Generalization Benefit of Normalization Layers:
  Sharpness Reduction
Understanding the Generalization Benefit of Normalization Layers: Sharpness Reduction
Kaifeng Lyu
Zhiyuan Li
Sanjeev Arora
FAtt
37
69
0
14 Jun 2022
Minimum sharpness: Scale-invariant parameter-robustness of neural
  networks
Minimum sharpness: Scale-invariant parameter-robustness of neural networks
Hikaru Ibayashi
Takuo Hamaguchi
Masaaki Imaizumi
25
5
0
23 Jun 2021
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp
  Minima
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima
N. Keskar
Dheevatsa Mudigere
J. Nocedal
M. Smelyanskiy
P. T. P. Tang
ODL
284
2,890
0
15 Sep 2016
The Loss Surfaces of Multilayer Networks
The Loss Surfaces of Multilayer Networks
A. Choromańska
Mikael Henaff
Michaël Mathieu
Gerard Ben Arous
Yann LeCun
ODL
179
1,185
0
30 Nov 2014
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