Hi Nat,
The reason for averaging at every time step (rather than doing k-best
list reranking on the sentence level) is the same reason why we
integrate new feature functions in Moses instead of just reranking the
k-best output: you make more search errors if you do your initial search
with a weak model, and then re-rank the k-best list with a stronger
model, and it is sensible to do the full search with the stronger model.
you can also do a weighted average if you want.
best wishes,
Rico
On 09/11/16 07:01, Nat Gillin wrote:
Dear Rico and Moses community,
Thanks for the response. Is there a reason why should there be an
average at every time step? Is the assumption that all networks
contributing to the ensembles are equal?
How is that different from training wider neural nets?
Sorry for the multiple questions.
Regards,
Nat
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