Translations:Dropout A Simple Way to Prevent Overfitting/7/en

• dropout regularization: A training procedure that randomly omits neurons during each forward and backward pass, preventing neurons from developing overly specialized co-adaptations.
• Ensemble interpretation: Theoretical motivation of dropout as approximate model averaging over $ 2^n $ possible thinned networks (where $ n $ is the number of droppable units), with shared weights.
• Comprehensive empirical evaluation: Demonstration of consistent improvements across diverse domains including vision, speech recognition, text classification, and computational biology.
• Practical guidelines: Recommendations for dropout rates ($ p = 0.5 $ for hidden units, $ p = 0.8 $ for input units) and interactions with other hyperparameters.