Understanding Dropout as an Optimization Trick

As one of standard approaches to train deep neural networks, dropout has been applied to regularize large models to avoid overfitting, and the improvement in performance by dropout has been explained as avoiding co-adaptation between nodes. However, when correlations between nodes are compared after...

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Veröffentlicht in:	arXiv.org 2019-10
Hauptverfasser:	Hahn, Sangchul, Choi, Heeyoul
Format:	Artikel
Sprache:	eng
Schlagworte:	Acceleration Activation Adaptation Back propagation Image classification Mathematical models Neural networks Nodes Optimization Optimization techniques Saturation
Online-Zugang:	Volltext
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