Papers with neural regression function

1 papers
Few-Shot Representation Learning for Out-Of-Vocabulary Words (P19-1)

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Challenge: Existing methods for learning word embedding assume there are enough occurrences for each word in the corpus to accurately estimate the representation of words.
Approach: They propose to fit a representation function to predict an oracle embedding vector based on limited contexts.
Outcome: The proposed model outperforms existing methods in constructing an accurate embedding for OOV words and improves downstream tasks when the embeddable is utilized.

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