408 citations · 554 across the 11 of their papers we have counts for
7 papers · 1 filter
SkyMask: Attack-agnostic Robust Federated Learning with Fine-grained Learnable Masks
Peishen Yan, Hao Wang, Tao Song +5
Federated Learning (FL) is becoming a popular paradigm for leveraging distributed data and preserving data privacy. However, due to the distributed characteristic, FL systems are v…
PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark
Jianqing Zhang, Yang Liu, Yang Hua +5
Amid the ongoing advancements in Federated Learning (FL), a machine learning paradigm that allows collaborative learning with data privacy protection, personalized FL (pFL)has gain…
Eliminating Domain Bias for Federated Learning in Representation Space
Jianqing Zhang, Yang Hua, Jian Cao +5
Recently, federated learning (FL) is popular for its privacy-preserving and collaborative learning abilities. However, under statistically heterogeneous scenarios, we observe that…
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…