25 citations · 67 across the 8 of their papers we have counts for
10 papers
Privacy-preserving Transfer Learning via Secure Maximum Mean Discrepancy
Bin Zhang, Cen Chen, Li Wang
The success of machine learning algorithms often relies on a large amount of high-quality data to train well-performed models. However, data is a valuable resource and are always h…
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning
Cen Chen, Bingzhe Wu, Minghui Qiu +2
Transfer learning is widely used for transferring knowledge from a source domain to the target domain where the labeled data is scarce. Recently, deep transfer learning has achieve…
Practical Privacy Preserving POI Recommendation
Chaochao Chen, Jun Zhou, Bingzhe Wu +4
Point-of-Interest (POI) recommendation has been extensively studied and successfully applied in industry recently. However, most existing approaches build centralized models on the…
Secret Sharing based Secure Regressions with Applications
Chaochao Chen, Liang Li, Wenjing Fang +6
Nowadays, the utilization of the ever expanding amount of data has made a huge impact on web technologies while also causing various types of security concerns. On one hand, potent…
Adapted tree boosting for Transfer Learning
Wenjing Fang, Chaochao Chen, Bowen Song +3
Secure online transaction is an essential task for e-commerce platforms. Alipay, one of the world's leading cashless payment platform, provides the payment service to both merchant…
Industrial Scale Privacy Preserving Deep Neural Network
Longfei Zheng, Chaochao Chen, Yingting Liu +6
Deep Neural Network (DNN) has been showing great potential in kinds of real-world applications such as fraud detection and distress prediction. Meanwhile, data isolation has become…