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Magnitude: A Fast, Efficient Universal Vector Embedding Utility Package
Ajay Patel
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Alexander Sands
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Chris Callison-Burch
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Marianna Apidianaki
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Paper Details:
Month: November
Year: 2018
Location: Brussels, Belgium
Venue:
EMNLP |
Citations
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No Citations Yet
https://www.sqlite.org/
http://www.numpy.org/
https://github.com/spotify/annoy
https://xxhash.org/
http://www.lz4.org/
https://pypi.org/project/pymagnitude/
https://github.com/plasticityai/
https://github.com/plasticityai/
https://www.tensorflow.org/
https://www.sqlite.org/datatype3.html
https://github.com/
https://doi.org/10
https://github.com/plasticityai/magnitude/blob/master/tests/benchmark.py
http://magnitude.plasticity.ai/word2vec+approx/GoogleNews-vectors-negative300
https://github.com/RaRe-Technologies/gensim-data
Field Of Study
Linguistic Trends
Embeddings
Syntax
Language
Multilingual
French
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News
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