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Dropout in Training Neural Networks: Flatness of Solution and Noise Structure

Dropout in Training Neural Networks: Flatness of Solution and Noise Structure

Zhongwang Zhang
Hanxu Zhou
Zhi-Qin John Xu
    ODL
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Papers citing "Dropout in Training Neural Networks: Flatness of Solution and Noise Structure"

3 / 3 papers shown
Title
Weight fluctuations in (deep) linear neural networks and a derivation of the inverse-variance flatness relation
Weight fluctuations in (deep) linear neural networks and a derivation of the inverse-variance flatness relation
Markus Gross
A. Raulf
Christoph Räth
51
0
0
23 Nov 2023
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
312
2,896
0
15 Sep 2016
Improving neural networks by preventing co-adaptation of feature detectors
Improving neural networks by preventing co-adaptation of feature detectors
Geoffrey E. Hinton
Nitish Srivastava
A. Krizhevsky
Ilya Sutskever
Ruslan Salakhutdinov
VLM
268
7,640
0
03 Jul 2012