19 citations · 63 across the 26 of their papers we have counts for
4 papers · 1 filter
Parallel Unlearning in Inherited Model Networks
Xiao Liu, Mingyuan Li, Guangsheng Yu +3
Unlearning is challenging in generic learning frameworks with the continuous growth and updates of models exhibiting complex inheritance relationships. This paper presents a novel…
A Secure Aggregation for Federated Learning on Long-Tailed Data
Yanna Jiang, Baihe Ma, Xu Wang +4
As a distributed learning, Federated Learning (FL) faces two challenges: the unbalanced distribution of training data among participants, and the model attack by Byzantine nodes. I…
Blockchained Federated Learning for Internet of Things: A Comprehensive Survey
Yanna Jiang, Baihe Ma, Xu Wang +5
The demand for intelligent industries and smart services based on big data is rising rapidly with the increasing digitization and intelligence of the modern world. This survey comp…
IronForge: An Open, Secure, Fair, Decentralized Federated Learning
Guangsheng Yu, Xu Wang, Caijun Sun +5
Federated learning (FL) provides an effective machine learning (ML) architecture to protect data privacy in a distributed manner. However, the inevitable network asynchrony, the ov…