Talk:Autoencoder: Difference between revisions

Revision as of 11:33, 18 March 2014

Revision as of 17:22, 13 January 2016

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==Answer: The outputs are the same as the inputs, i.e. y_i = x_i. The autoencoder tries to learn the identity function. Although it might seem that if the number of hidden units >= the number of input units (/output units) the resulting weights would be the trivial identity, in practice this does not turn out to be the case (probably due to the fact that the weights start so small). Sparse autoencoders, where a limited number of hidden units can be activated at once, avoid this problem even in theory. [[Special:Contributions/216.169.216.1|216.169.216.1]] ([[User talk:216.169.216.1|talk]]) 16:47, 17 September 2013 (UTC) Dave Rimshnick

==Where is the structure section taken from?""

The description is quite clean and I was wondering if there were any book sources that could be added as reference where a similar approach in describing the autoencoder is taken.