Self-Taught Learning

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(Overview)
(Overview)
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supervised learning on that labeled data to solve the classification task.
supervised learning on that labeled data to solve the classification task.
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These ideas are probably most powerful in settings where we have a lot of
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These ideas probably have the most powerful effects in problems where we have a lot of
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unlabeled data, and a relatively smaller amount of labeled data.  However,
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unlabeled data, and a smaller amount of labeled data.  However,
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these models often given good results even if we have only
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they typically give good results even if we have only
labeled data (in which case we usually perform the feature learning step using
labeled data (in which case we usually perform the feature learning step using
the labeled data, but ignoring the labels).
the labeled data, but ignoring the labels).

Revision as of 23:25, 10 May 2011

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