Papers with mixture of von Mises-Fisher

1 papers
Word and Document Embedding with vMF-Mixture Priors on Context Word Vectors (P19-1)

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Challenge: Word embedding models typically learn two types of vectors: target word vectors and context word vector.
Approach: They propose to explicitly impose a cluster structure on context word vectors to improve word embedding models.
Outcome: The proposed model improves word embedding models qualitatively by imposing a cluster structure on the set of context word vectors.

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