Questions tagged [dropout]

Dropout is a technique to reduce overfitting during the training phase of a neural network.

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How exactly does DropOut work with convolutional layers?

Dropout (paper, explanation) sets the output of some neurons to zero. So for a MLP, you could have the following architecture for the Iris flower dataset: ...
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Dropout backpropagation implementation details

Just to summarize Understanding dropout and gradient descent and https://stats.stackexchange.com/questions/207481/dropout-backpropagation-implementation Suppose I need to implement inverted dropout ...
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1answer
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Correct order of operations involved into Dropout

Suppose we have CNN with any hidden layer with activation followed by dropout layer. What is the correct precedence of activation and dropout operation if dropout implementation is inverted dropout ...
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1answer
2k views

Why does dropout ruin my accuracy in CNN?

I've build a CNN in Tensorflow with 2 conv layers, 1 pool layer and 2 FC layers. When I don't use dropout I get 98% accuracy on training dataset and 90% on test dataset. But, when I do use dropout, I ...
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1answer
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Does dropout require multiple passes of the same data set, as a sort of ensemble method?

I'm a bit confused about dropout -- on one tutorial, it was described as basically an 'ensemble method' of sorts. This implies that you might need to create an ensemble of networks. Is this the case, ...
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2answers
176 views

Are there studies which examine dropout vs other regularizations?

Are there any papers published which show differences of the regularization methods for neural networks, preferably on different domains (or at least different datasets)? I am asking because I ...

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