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The network
learns a density model for
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unlabeled digit
images. When we generate
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from the model we
get things that look like
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real digits of
all classes.
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But do the hidden
features really help with
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digit
discrimination?
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Add 10 softmaxed
units to the top and do
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backpropagation.
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