Jiapeng Wu

NodePiece: Compositional and Parameter-Efficient Representations of\n Large Knowledge Graphs

2021 · arXiv (Cornell University)

Conventional representation learning algorithms for knowledge graphs (KG) map\neach entity to a unique embedding vector. Such a shallow lookup results in a\nlinear growth of memory consumption for storing the embedding matrix and incurs\nhigh computational costs …