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After we have
learned all the layers greedily, the weights
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in the lower
layers will no longer be optimal. We can
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improve them in
two ways:
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Untie
the recognition weights from the generative
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weights
and learn recognition weights that take into
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account
the non-complementary prior implemented by
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the
weights in higher layers.
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– |
Improve
the generative weights to take into account
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the
non-complementary priors implemented by the
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weights
in higher layers.
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What algorithm
should we use for improving on the
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weights that are
learned greedily?
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