408 citations · 540 across the 11 of their papers we have counts for
11 papers
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning
Jianqing Zhang, Yang Hua, Hao Wang +5
Federated Learning (FL) is popular for its privacy-preserving and collaborative learning capabilities. Recently, personalized FL (pFL) has received attention for its ability to add…
Chrion: Optimizing Recurrent Neural Network Inference by Collaboratively Utilizing CPUs and GPUs
Zinuo Cai, Hao Wang, Tao Song +3
Deploying deep learning models in cloud clusters provides efficient and prompt inference services to accommodate the widespread application of deep learning. These clusters are usu…
FedCP: Separating Feature Information for Personalized Federated Learning via Conditional Policy
Jianqing Zhang, Yang Hua, Hao Wang +4
Recently, personalized federated learning (pFL) has attracted increasing attention in privacy protection, collaborative learning, and tackling statistical heterogeneity among clien…
Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples
Chumeng Liang, Xiaoyu Wu, Yang Hua +6
Recently, Diffusion Models (DMs) boost a wave in AI for Art yet raise new copyright concerns, where infringers benefit from using unauthorized paintings to train DMs to generate no…
FedALA: Adaptive Local Aggregation for Personalized Federated Learning
Jianqing Zhang, Yang Hua, Hao Wang +4
A key challenge in federated learning (FL) is the statistical heterogeneity that impairs the generalization of the global model on each client. To address this, we propose a method…
DuVisor: a User-level Hypervisor Through Delegated Virtualization
Jiahao Chen, Dingji Li, Zeyu Mi +4
Today's mainstream virtualization systems comprise of two cooperative components: a kernel-resident driver that accesses virtualization hardware and a user-level helper process tha…