10 citations · 11 across the 3 of their papers we have counts for
3 papers
cs.LG2023
Temporal Gradient Inversion Attacks with Robust Optimization
Bowen Li, Hanlin Gu, Ruoxin Chen +5
Federated Learning (FL) has emerged as a promising approach for collaborative model training without sharing private data. However, privacy concerns regarding information exchanged…
cs.DC2022★ 1 cited
A Smart Contract based Crowdfunding Mechanism for Hierarchical Federated Learning
Hongze Liu, Jie Li, Shijing Yuan +2
Hierarchical Federated Learning (HFL) is introduced as a promising technique that allows model owners to fully exploit computational resources and bandwidth resources to train the…
cs.LG2021★ 10 cited
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…