Subsampling is effective in Knowledge Graph Embedding (KGE) for reducing...
Recently, in the field of recommendation systems, linear regression
(aut...
Wikipedia has high-quality articles on a variety of topics and has been ...
In this paper, we propose a table and image generation task to verify ho...
In this article, we explain the recent advance of subsampling methods in...
Negative sampling (NS) loss plays an important role in learning knowledg...
In knowledge graph embedding, the theoretical relationship between the
s...
The global pandemic of COVID-19 has made the public pay close attention ...
Methods based on vector embeddings of knowledge graphs have been activel...
Bilinear diagonal models for knowledge graph embedding (KGE), such as
Di...
Tensor factorization has become an increasingly popular approach to know...
Currently, the biaffine classifier has been attracting attention as a me...
Embedding-based methods for knowledge base completion (KBC) learn
repres...