16 citations · 19 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 16 cited
Dropout Reduces Underfitting
Zhuang Liu, Zhiqiu Xu, Joseph Jin +2
Introduced by Hinton et al. in 2012, dropout has stood the test of time as a regularizer for preventing overfitting in neural networks. In this study, we demonstrate that dropout c…
cs.LG2022★ 2 cited
Implicit regularization of dropout
Zhongwang Zhang, Zhi-Qin John Xu
It is important to understand how dropout, a popular regularization method, aids in achieving a good generalization solution during neural network training. In this work, we presen…
cs.LG2021★ 1 cited
Dropout in Training Neural Networks: Flatness of Solution and Noise Structure
Zhongwang Zhang, Hanxu Zhou, Zhi-Qin John Xu
It is important to understand how the popular regularization method dropout helps the neural network training find a good generalization solution. In this work, we show that the tr…