Binarized Canonical Polyadic Decomposition for Knowledge Graph Completion

no code implementations • 4 Dec 2019 • Koki Kishimoto, Katsuhiko Hayashi, Genki Akai, Masashi Shimbo

Methods based on vector embeddings of knowledge graphs have been actively pursued as a promising approach to knowledge graph completion. However, embedding models generate storage-inefficient representations, particularly when the number of entities and relations, and the dimensionality of the real-valued embedding vectors are large.

Binarized Knowledge Graph Embeddings

2 code implementations • 8 Feb 2019 • Koki Kishimoto, Katsuhiko Hayashi, Genki Akai, Masashi Shimbo, Kazunori Komatani

This limitation is expected to become more stringent as existing knowledge graphs, which are already huge, keep steadily growing in scale.

Knowledge Graph Embeddings Quantization +1