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Results tagged with word-embeddings
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user 54721
Word embedding is the collective name for a set of language modeling and feature learning techniques in NLP where words are mapped to vectors of real numbers in a low dimensional space, relative to the vocabulary size.
5
votes
1
answer
2k
views
Why does all of NLP literature use Noise contrastive estimation loss for negative sampling i...
A sampled softmax function is like a regular softmax but randomly selects a given number of 'negative' samples.
This is difference than NCE Loss, which doesn't use a softmax at all, it uses a logistic …
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