72 citations · 197 across the 19 of their papers we have counts for
5 papers · 1 filter
Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignment
Qijie Ding, Daokun Zhang, Jie Yin
Entity alignment aims to discover unique equivalent entity pairs with the same meaning across different knowledge graphs (KGs). Existing models have focused on projecting KGs into…
Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion
Han Wu, Jie Yin, Bala Rajaratnam +1
Knowledge graphs (KGs) are powerful in terms of their inference abilities, but are also notorious for their incompleteness and long-tail distribution of relations. To address these…
LADDER: Latent Boundary-guided Adversarial Training
Xiaowei Zhou, Ivor W. Tsang, Jie Yin
Deep Neural Networks (DNNs) have recently achieved great success in many classification tasks. Unfortunately, they are vulnerable to adversarial attacks that generate adversarial e…
Informative Pseudo-Labeling for Graph Neural Networks with Few Labels
Yayong Li, Jie Yin, Ling Chen
Graph Neural Networks (GNNs) have achieved state-of-the-art results for semi-supervised node classification on graphs. Nevertheless, the challenge of how to effectively learn GNNs…
Link Prediction with Contextualized Self-Supervision
Daokun Zhang, Jie Yin, Philip S. Yu
Link prediction aims to infer the link existence between pairs of nodes in networks/graphs. Despite their wide application, the success of traditional link prediction algorithms is…