Shakedrop Regularization for Deep Residual Learning
Overfitting is a crucial problem in deep neural networks, even in the latest network architectures. In this paper, to relieve the overfitting effect of ResNet and its improvements (i.e., Wide ResNet, PyramidNet, and ResNeXt), we propose a new regularization method called ShakeDrop regularization. Sh...
Main Authors: | Yoshihiro Yamada, Masakazu Iwamura, Takuya Akiba, Koichi Kise |
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Format: | Article |
Language: | English |
Published: |
IEEE
2019-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8936428/ |
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