66 citations · 68 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 2 cited
FedCAT: Towards Accurate Federated Learning via Device Concatenation
Ming Hu, Tian Liu, Zhiwei Ling +2
As a promising distributed machine learning paradigm, Federated Learning (FL) enables all the involved devices to train a global model collaboratively without exposing their local…
cs.LG2022
Towards Fast and Accurate Federated Learning with non-IID Data for Cloud-Based IoT Applications
Tian Liu, Jiahao Ding, Ting Wang +2
As a promising method of central model training on decentralized device data while securing user privacy, Federated Learning (FL)is becoming popular in Internet of Things (IoT) des…
cs.LG2020★ 66 cited
FDA3 : Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications
Yunfei Song, Tian Liu, Tongquan Wei +3
Along with the proliferation of Artificial Intelligence (AI) and Internet of Things (IoT) techniques, various kinds of adversarial attacks are increasingly emerging to fool Deep Ne…