20 citations · 76 across the 27 of their papers we have counts for
5 papers · 2 filters
PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation
Weiqin Yang, Jiawei Chen, Xin Xin +5
Softmax Loss (SL) is widely applied in recommender systems (RS) and has demonstrated effectiveness. This work analyzes SL from a pairwise perspective, revealing two significant lim…
Towards Dynamic Graph Neural Networks with Provably High-Order Expressive Power
Zhe Wang, Tianjian Zhao, Zhen Zhang +5
Dynamic Graph Neural Networks (DyGNNs) have garnered increasing research attention for learning representations on evolving graphs. Despite their effectiveness, the limited express…
Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding
Zhe Wang, Sheng Zhou, Jiawei Chen +5
Learning effective representations for Continuous-Time Dynamic Graphs (CTDGs) has garnered significant research interest, largely due to its powerful capabilities in modeling compl…
Motif-driven Subgraph Structure Learning for Graph Classification
Zhiyao Zhou, Sheng Zhou, Bochao Mao +5
To mitigate the suboptimal nature of graph structure, Graph Structure Learning (GSL) has emerged as a promising approach to improve graph structure and boost performance in downstr…
Knowledge Translation: A New Pathway for Model Compression
Wujie Sun, Defang Chen, Jiawei Chen +3
Deep learning has witnessed significant advancements in recent years at the cost of increasing training, inference, and model storage overhead. While existing model compression met…