6 citations · 6 across the 2 of their papers we have counts for
2 papers
cs.LG2024
Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuning
Jingyuan Zhang, Yiyang Duan, Shuaicheng Niu +2
Federated Domain Adaptation (FDA) is a Federated Learning (FL) scenario where models are trained across multiple clients with unique data domains but a shared category space, witho…
cs.CR2024★ 6 cited
Enhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense
Wenjie Li, Kai Fan, Jingyuan Zhang +3
Federated Learning (FL) is a promising privacy-preserving machine learning paradigm that allows data owners to collaboratively train models while keeping their data localized. Desp…