4 citations · 7 across the 5 of their papers we have counts for
5 papers
LPS-GNN : Deploying Graph Neural Networks on Graphs with 100-Billion Edges
Xu Cheng, Liang Yao, Feng He +6
Graph Neural Networks (GNNs) have emerged as powerful tools for various graph mining tasks, yet existing scalable solutions often struggle to balance execution efficiency with pred…
Friend Ranking in Online Games via Pre-training Edge Transformers
Liang Yao, Jiazhen Peng, Shenggong Ji +4
Friend recall is an important way to improve Daily Active Users (DAU) in online games. The problem is to generate a proper lost friend ranking list essentially. Traditional friend…
A Topological Centrality Measure for Directed Networks
Fenghuan He
Given a directed network , we are interested in studying the qualitative features of which govern how perturbations propagate across . Various classical centrality…
SCR: Training Graph Neural Networks with Consistency Regularization
Chenhui Zhang, Yufei He, Yukuo Cen +7
We present the SCR framework for enhancing the training of graph neural networks (GNNs) with consistency regularization. Regularization is a set of strategies used in Machine Learn…
Initialization for Network Embedding: A Graph Partition Approach
Wenqing Lin, Feng He, Faqiang Zhang +2
Network embedding has been intensively studied in the literature and widely used in various applications, such as link prediction and node classification. While previous work focus…