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63 views

What parallelization methods can make neural nets train faster?

A fairly straightforward way (on a theoretical level, at least) of parallelizing artifical neural networks (ANNs) would be to divy up the batches of training examples during every epoch so that ...
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31 views

How do you feed sets of connected data elements to an artificial neural network?

I'm currently working on a neural network to try to predict movements of electricity prices in a big city with multiple power companies to choose from. I know from a friend in the industry that power ...
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57 views

How to evaluate a recurrent connection in an artificial neural network?

I just can't understand how should I compute the output of a neural network, which contains a recurrent connection. So here is an example: (i_1,2 are the input values, w_1,2,3,r are the ...
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0answers
201 views

Neural network converges to 0.5 for XoR

I'm coding a neural network in C for an OCR project. Before testing with character recognition, I'm making it learn the XoR operation. Although, the results I'n getting always converges to 0.5 instead ...
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31 views

Is sparsity parameter really useful?

To make a sparse autoencoder,one way is add something to the function we want to minimize,which the further do average activity of hidden units to a sparsity parameter,the bigger your added thing will ...