13 citations · 29 across the 5 of their papers we have counts for
5 papers
Privacy-preserving design of graph neural networks with applications to vertical federated learning
Ruofan Wu, Mingyang Zhang, Lingjuan Lyu +6
The paradigm of vertical federated learning (VFL), where institutions collaboratively train machine learning models via combining each other's local feature or label information, h…
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs
Sheng Tian, Jihai Dong, Jintang Li +7
Anomaly detection aims to distinguish abnormal instances that deviate significantly from the majority of benign ones. As instances that appear in the real world are naturally conne…
Huatuo-26M, a Large-scale Chinese Medical QA Dataset
Jianquan Li, Xidong Wang, Xiangbo Wu +6
In this paper, we release a largest ever medical Question Answering (QA) dataset with 26 million QA pairs. We benchmark many existing approaches in our dataset in terms of both ret…
Differentially Private Learning with Per-Sample Adaptive Clipping
Tianyu Xia, Shuheng Shen, Su Yao +4
Privacy in AI remains a topic that draws attention from researchers and the general public in recent years. As one way to implement privacy-preserving AI, differentially private le…
Scalable Data Cube Analysis over Big Data
Zhengkui Wang, Yan Chu, Kian-Lee Tan +3
Data cubes are widely used as a powerful tool to provide multidimensional views in data warehousing and On-Line Analytical Processing (OLAP). However, with increasing data sizes, i…