137 citations · 169 across the 4 of their papers we have counts for
4 papers
Scalable and Sparsity-Aware Privacy-Preserving K-means Clustering with Application to Fraud Detection
Yingting Liu, Chaochao Chen, Jamie Cui +2
K-means is one of the most widely used clustering models in practice. Due to the problem of data isolation and the requirement for high model performance, how to jointly build prac…
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…
Privacy Preserving PCA for Multiparty Modeling
Yingting Liu, Chaochao Chen, Longfei Zheng +4
In this paper, we present a general multiparty modeling paradigm with Privacy Preserving Principal Component Analysis (PPPCA) for horizontally partitioned data. PPPCA can accomplis…
Federated Forest
Yang Liu, Yingting Liu, Zhijie Liu +3
Most real-world data are scattered across different companies or government organizations, and cannot be easily integrated under data privacy and related regulations such as the Eu…