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For questions related to the concept of dropout, which refers to the dropping out units in a neural network (NN), during the training of the NN, so that to avoid overfitting. The dropout method is a regularisation technique, which was introduced in "Dropout: A Simple Way to Prevent Neural Networks from Overfitting" (2014) by Nitish Srivastava et al.

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The design was tailored for use in conjunction with dropout (then recently introduced) and resulted of course in state-of-the-art results on benchmarks like CIFAR-10 and SVHN. … Five years later, dropout is definitely still in the game, but what about maxout? …
asked Jul 10 '18 by user209974