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They always
looked like a really nice way to do
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non-linear
dimensionality reduction:
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They
provide mappings both ways
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The
learning time is linear (or better) in the
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number
of training cases.
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The
final model is compact and fast.
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But it turned
out to be very very difficult to
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optimize deep
autoencoders using backprop.
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We
now have a much better way to optimize
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them.
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