Single Training Dimension Selection for Word Embedding with PCA

IJCNLP 2019 Yu Wang

In this paper, we present a fast and reliable method based on PCA to select the number of dimensions for word embeddings. First, we train one embedding with a generous upper bound (e.g. 1,000) of dimensions... (read more)

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