19 citations · 22 across the 5 of their papers we have counts for
5 papers
OFL-W3: A One-shot Federated Learning System on Web 3.0
Linshan Jiang, Moming Duan, Bingsheng He +4
Federated Learning (FL) addresses the challenges posed by data silos, which arise from privacy, security regulations, and ownership concerns. Despite these barriers, FL enables the…
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…
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…
Knowing Where and What: Unified Word Block Pretraining for Document Understanding
Song Tao, Zijian Wang, Tiantian Fan +2
Due to the complex layouts of documents, it is challenging to extract information for documents. Most previous studies develop multimodal pre-trained models in a self-supervised wa…