7 citations · 9 across the 8 of their papers we have counts for
5 papers · 1 filter
MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning
Yun Zhu, Haizhou Shi, Zhenshuo Zhang +1
In this work, we investigate the problem of out-of-distribution (OOD) generalization for unsupervised learning methods on graph data. This scenario is particularly challenging beca…
Structure-Aware Group Discrimination with Adaptive-View Graph Encoder: A Fast Graph Contrastive Learning Framework
Zhenshuo Zhang, Yun Zhu, Haizhou Shi +1
Albeit having gained significant progress lately, large-scale graph representation learning remains expensive to train and deploy for two main reasons: (i) the repetitive computati…
SGL-PT: A Strong Graph Learner with Graph Prompt Tuning
Yun Zhu, Jianhao Guo, Siliang Tang
Recently, much exertion has been paid to design graph self-supervised methods to obtain generalized pre-trained models, and adapt pre-trained models onto downstream tasks through f…
RoSA: A Robust Self-Aligned Framework for Node-Node Graph Contrastive Learning
Yun Zhu, Jianhao Guo, Fei Wu +1
Graph contrastive learning has gained significant progress recently. However, existing works have rarely explored non-aligned node-node contrasting. In this paper, we propose a nov…
Active Learning for Product Type Ontology Enhancement in E-commerce
Yun Zhu, Sayyed M. Zahiri, Jiaqi Wang +2
Entity-based semantic search has been widely adopted in modern search engines to improve search accuracy by understanding users' intent. In e-commerce, an accurate and complete pro…