Corpus ID: 211259165

Distributed Training of Embeddings using Graph Analytics

@article{Gill2019DistributedTO,
  title={Distributed Training of Embeddings using Graph Analytics},
  author={G. Gill and Roshan Dathathri and S. Maleki and Madan Musuvathi and Todd Mytkowicz and Olli Saarikivi The University of Texas at Austin and M. Research},
  journal={arXiv: Learning},
  year={2019}
}
Many applications today, such as NLP, network analysis, and code analysis, rely on semantically embedding objects into low-dimensional fixed-length vectors. Such embeddings naturally provide a way to perform useful downstream tasks, such as identifying relations among objects or predicting objects for a given context, etc. Unfortunately, the training necessary for accurate embeddings is usually computationally intensive and requires processing large amounts of data. Furthermore, distributing… Expand

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