33 citations · 162 across the 52 of their papers we have counts for
4 papers · 1 filter
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…
FedIPR: Ownership Verification for Federated Deep Neural Network Models
Bowen Li, Lixin Fan, Hanlin Gu +2
Federated learning models are collaboratively developed upon valuable training data owned by multiple parties. During the development and deployment of federated models, they are e…
Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack
Ding Sheng Ong, Chee Seng Chan, Kam Woh Ng +2
Ever since Machine Learning as a Service (MLaaS) emerges as a viable business that utilizes deep learning models to generate lucrative revenue, Intellectual Property Right (IPR) ha…