10 citations · 11 across the 3 of their papers we have counts for
4 papers
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…
FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders
Hanlin Gu, Lixin Fan, Xingxing Tang +1
This paper proposes a general spectral analysis framework that thwarts a security risk in federated Learning caused by groups of malicious Byzantine attackers or colluders, who con…
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…
Data-Driven Tight Frame for Cryo-EM Image Denoising and Conformational Classification
Yin Xian, Hanlin Gu, Wei Wang +4
The cryo-electron microscope (cryo-EM) is increasingly popular these years. It helps to uncover the biological structures and functions of macromolecules. In this paper, we address…