Closed Form Word Embedding Alignment

4 Jun 2018Sunipa DevSafia HassanJeff M. Phillips

We develop a family of techniques to align word embeddings which are derived from different source datasets or created using different mechanisms (e.g., GloVe or word2vec). Our methods are simple and have a closed form to optimally rotate, translate, and scale to minimize root mean squared errors or maximize the average cosine similarity between two embeddings of the same vocabulary into the same dimensional space... (read more)

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