Expanding Holographic Embeddings for Knowledge Completion

@inproceedings{Xue2018ExpandingHE,
  title={Expanding Holographic Embeddings for Knowledge Completion},
  author={Yexiang Xue and Yang Yuan and Zhitian Xu and Ashutosh Sabharwal},
  booktitle={NeurIPS},
  year={2018}
}
Neural models operating over structured spaces such as knowledge graphs require a continuous embedding of the discrete elements of this space (such as entities) as well as the relationships between them. Relational embeddings with high expressivity, however, have high model complexity, making them computationally difficult to train. We propose a new family of embeddings for knowledge graphs that interpolate between a method with high model complexity and one, namely Holographic embeddings (HOLE… CONTINUE READING

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