Autoencoders and Sparsity

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m (minor rephrase)
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So far, we have described the application of neural networks to supervised learning, in which we have labeled
So far, we have described the application of neural networks to supervised learning, in which we have labeled
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training examples.  Now suppose we have only unlabeled training examples set <math>\textstyle \{x^{(1)}, x^{(2)}, x^{(3)}, \ldots\}</math>,
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training examples.  Now suppose we have only a set of unlabeled training examples <math>\textstyle \{x^{(1)}, x^{(2)}, x^{(3)}, \ldots\}</math>,
where <math>\textstyle x^{(i)} \in \Re^{n}</math>.  An
where <math>\textstyle x^{(i)} \in \Re^{n}</math>.  An
'''autoencoder''' neural network is an unsupervised learning algorithm that applies backpropagation,
'''autoencoder''' neural network is an unsupervised learning algorithm that applies backpropagation,

Revision as of 22:53, 21 September 2011

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