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a new area of Machine Learning research concerned with the technologies used for learning hierarchical representations of data, mainly done with deep neural networks (i.e. networks with two or more hidden layers), but also with some sort of Probabilistic Graphical Models.

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Can the vanishing gradient problem be solved by multiplying the input of tanh with a coeffic...

Thanks to everyone for their great answers - they've really helped in thinking about this problem - and I recommend anyone interested in the problem having a look - but there's a much simpler route to …
zephyr's user avatar
  • 131
8 votes
4 answers
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Can the vanishing gradient problem be solved by multiplying the input of tanh with a coeffic...

To my understanding, the vanishing gradient problem occurs when training neural networks when the gradient of each activation function is less than 1 such that when corrections are back-propagated thr …
zephyr's user avatar
  • 131