activity
20172023
most citedUncovering Insurance Fraud Conspiracy with Network Learning

49 citations · 156 across the 15 of their papers we have counts for

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Showing 2020Show all

15 papers · 1 filter

cs.LG20205 cited

ASFGNN: Automated Separated-Federated Graph Neural Network

Longfei Zheng, Jun Zhou, Chaochao Chen +3

Graph Neural Networks (GNNs) have achieved remarkable performance by taking advantage of graph data. The success of GNN models always depends on rich features and adjacent relation…

cs.CL202012 cited

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…

cs.CR20204 cited

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…

cs.LG20204 cited

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…

cs.LG20202 cited

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…

cs.LG2020

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…