62 citations · 537 across the 44 of their papers we have counts for
44 papers
DGI: Easy and Efficient Inference for GNNs
Peiqi Yin, Xiao Yan, Jinjing Zhou +5
While many systems have been developed to train Graph Neural Networks (GNNs), efficient model inference and evaluation remain to be addressed. For instance, using the widely adopte…
A Representation Learning Framework for Property Graphs
Yifan Hou, Hongzhi Chen, Changji Li +2
Representation learning on graphs, also called graph embedding, has demonstrated its significant impact on a series of machine learning applications such as classification, predict…
Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
Yongqiang Chen, Han Yang, Yonggang Zhang +4
Recently Graph Injection Attack (GIA) emerges as a practical attack scenario on Graph Neural Networks (GNNs), where the adversary can merely inject few malicious nodes instead of m…
G-Tran: Making Distributed Graph Transactions Fast
Hongzhi Chen, Changji Li, Chenguang Zheng +4
Graph transaction processing raises many unique challenges such as random data access due to the irregularity of graph structures, low throughput and high abort rate due to the rel…
Calibrating and Improving Graph Contrastive Learning
Kaili Ma, Haochen Yang, Han Yang +2
Graph contrastive learning algorithms have demonstrated remarkable success in various applications such as node classification, link prediction, and graph clustering. However, in u…
The item selection problem for user cold-start recommendation
Yitong Meng, Jie Liu, Xiao Yan +1
When a new user just signs up on a website, we usually have no information about him/her, i.e. no interaction with items, no user profile and no social links with other users. Unde…