 |
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|
|
|
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|
|
|
|
|
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| • |
A directed
module also converts its data
|
|
|
distribution
into an aggregated posterior
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|
– |
Task
1 is now harder because the
|
|
|
posterior
for each training case is non-
|
|
factorial.
|
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|
– |
Task
2 is performed using an
|
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independent
prior. This is a bad
|
|
|
approximation
unless the aggregated
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|
posterior
is close to factorial.
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|
| • |
A directed
module attempts to make the
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|
aggregated
posterior factorial in one step.
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|
– |
This
is too difficult and leads to a bad
|
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|
compromise.
There is no guarantee
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|
that
the aggregated posterior is easier
|
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|
to
model than the data distribution.
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|
