all AI news
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion. (arXiv:2209.01205v1 [cs.LG])
Sept. 5, 2022, 1:14 a.m. | Han Wu, Jianyuan Guo, Bala Rajaratnam, Jie Yin
cs.CV updates on arXiv.org arxiv.org
Knowledge graphs (KGs) are known for their large scale and knowledge
inference ability, but are also notorious for the incompleteness associated
with them. Due to the long-tail distribution of the relations in KGs, few-shot
KG completion has been proposed as a solution to alleviate incompleteness and
expand the coverage of KGs. It aims to make predictions for triplets involving
novel relations when only a few training triplets are provided as reference.
Previous methods have mostly focused on designing local neighbor …
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Senior AI & Data Engineer
@ Bertelsmann | Kuala Lumpur, 14, MY, 50400
Analytics Engineer
@ Reverse Tech | Philippines - Remote