2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.AI2024★ 1 cited
Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective
Yujie Mo, Zhihe Lu, Runpeng Yu +2
Self-supervised heterogeneous graph learning (SHGL) has shown promising potential in diverse scenarios. However, while existing SHGL methods share a similar essential with clusteri…
cs.LG2024★ 2 cited
HG-Adapter: Improving Pre-Trained Heterogeneous Graph Neural Networks with Dual Adapters
Yujie Mo, Runpeng Yu, Xiaofeng Zhu +1
The "pre-train, prompt-tuning'' paradigm has demonstrated impressive performance for tuning pre-trained heterogeneous graph neural networks (HGNNs) by mitigating the gap between pr…
cs.LG2023
Robust Long-Tailed Learning via Label-Aware Bounded CVaR
Hong Zhu, Runpeng Yu, Xing Tang +3
Data in the real-world classification problems are always imbalanced or long-tailed, wherein the majority classes have the most of the samples that dominate the model training. In…