358 citations · 1.1k across the 26 of their papers we have counts for
5 papers · 1 filter
Batch Label Inference and Replacement Attacks in Black-Boxed Vertical Federated Learning
Yang Liu, Tianyuan Zou, Yan Kang +4
In a vertical federated learning (VFL) scenario where features and model are split into different parties, communications of sample-specific updates are required for correct gradie…
Privacy-preserving Federated Adversarial Domain Adaption over Feature Groups for Interpretability
Yan Kang, Yang Liu, Yuezhou Wu +2
We present a novel privacy-preserving federated adversarial domain adaptation approach () to address an under-studied but practical cross-silo federated domain adap…
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning
Yuezhou Wu, Yan Kang, Jiahuan Luo +2
Federated learning (FL) aims to protect data privacy by enabling clients to build machine learning models collaboratively without sharing their private data. Recent works demonstra…
SecureBoost+: Large Scale and High-Performance Vertical Federated Gradient Boosting Decision Tree
Tao Fan, Weijing Chen, Guoqiang Ma +3
Gradient boosting decision tree (GBDT) is an ensemble machine learning algorithm, which is widely used in industry, due to its good performance and easy interpretation. Due to the…
Federated Deep Learning with Bayesian Privacy
Hanlin Gu, Lixin Fan, Bowen Li +3
Federated learning (FL) aims to protect data privacy by cooperatively learning a model without sharing private data among users. For Federated Learning of Deep Neural Network with…