Translations:Dropout A Simple Way to Prevent Overfitting/20/en

• MNIST (handwritten digits): Error reduced from 1.60% to 1.25% with dropout on a standard feedforward network.
• CIFAR-10/CIFAR-100: Significant error reductions on convolutional networks; relative improvement of approximately 15-25% on CIFAR-100.
• SVHN (Street View House Numbers): Error reduced from 2.80% to 2.68%.
• ImageNet: dropout improved the top-1 error of a large convolutional network by approximately 2 percentage points.
• TIMIT (speech recognition): Consistent improvements across various architecture sizes.
• Reuters (text classification): Improved performance on a bag-of-words text classification task.