Self-Taught Learning to Deep Networks

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(Overview)
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In the previous section, you used an autoencoder to learn features that were then fed as input  
In the previous section, you used an autoencoder to learn features that were then fed as input  
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to a softmax or logistic regression classifier.  There, the features were learned using
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to a softmax or logistic regression classifier.  In that method, the features were learned using
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only unlabeled data.  In this section, we show how you can  '''fine-tune''' or further improve  
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only unlabeled data.  In this section, we describe how you can  '''fine-tune''' and further improve  
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the learned features using the labeled data.  When you have a large amount of labeled
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the learned features using labeled data.  When you have a large amount of labeled
training data, this can significantly improve your classifier's performance.
training data, this can significantly improve your classifier's performance.

Revision as of 05:46, 13 May 2011

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