49 citations · 134 across the 12 of their papers we have counts for
18 papers
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…
Unpack Local Model Interpretation for GBDT
Wenjing Fang, Jun Zhou, Xiaolong Li +1
A gradient boosting decision tree (GBDT), which aggregates a collection of single weak learners (i.e. decision trees), is widely used for data mining tasks. Because GBDT inherits t…
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…
Privacy Preserving Point-of-interest Recommendation Using Decentralized Matrix Factorization
Chaochao Chen, Ziqi Liu, Peilin Zhao +2
Points of interest (POI) recommendation has been drawn much attention recently due to the increasing popularity of location-based networks, e.g., Foursquare and Yelp. Among the exi…