Papers with beam approximation

1 papers
Surprisingly Easy Hard-Attention for Sequence to Sequence Learning (D18-1)

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Challenge: Existing attention mechanisms are hard and hard, but they are more accurate when trained.
Approach: They propose to use a beam approximation of the joint distribution between attention and output to train sequence to sequence learning.
Outcome: The proposed method is compared to existing attention mechanisms on five translation tasks and shows consistent gains on the same tasks.

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