9 citations · 21 across the 26 of their papers we have counts for
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cs.AI2022★ 2 cited
Subsampling for Knowledge Graph Embedding Explained
Hidetaka Kamigaito, Katsuhiko Hayashi
In this article, we explain the recent advance of subsampling methods in knowledge graph embedding (KGE) starting from the original one used in word2vec.
cs.LG2022★ 9 cited
Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning
Hidetaka Kamigaito, Katsuhiko Hayashi
Negative sampling (NS) loss plays an important role in learning knowledge graph embedding (KGE) to handle a huge number of entities. However, the performance of KGE degrades withou…