6 citations · 9 across the 3 of their papers we have counts for
3 papers
cs.DC2021★ 1 cited
DFOGraph: An I/O- and Communication-Efficient System for Distributed Fully-out-of-Core Graph Processing
Jiping Yu, Wei Qin, Xiaowei Zhu +4
With the magnitude of graph-structured data continually increasing, graph processing systems that can scale-out and scale-up are needed to handle extreme-scale datasets. While exis…
cs.LG2021★ 6 cited
Heterogeneous Similarity Graph Neural Network on Electronic Health Records
Zheng Liu, Xiaohan Li, Hao Peng +2
Mining Electronic Health Records (EHRs) becomes a promising topic because of the rich information they contain. By learning from EHRs, machine learning models can be built to help…
cs.IR2021★ 2 cited
Dynamic Graph Collaborative Filtering
Xiaohan Li, Mengqi Zhang, Shu Wu +3
Dynamic recommendation is essential for modern recommender systems to provide real-time predictions based on sequential data. In real-world scenarios, the popularity of items and i…