14 citations · 18 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
FissionVAE: Federated Non-IID Image Generation with Latent Space and Decoder Decomposition
Chen Hu, Hanchi Ren, Jingjing Deng +2
Federated learning is a machine learning paradigm that enables decentralized clients to collaboratively learn a shared model while keeping all the training data local. While consid…
cs.LG2023★ 3 cited
Gradient Leakage Defense with Key-Lock Module for Federated Learning
Hanchi Ren, Jingjing Deng, Xianghua Xie
Federated Learning (FL) is a widely adopted privacy-preserving machine learning approach where private data remains local, enabling secure computations and the exchange of local mo…
cs.CV2020★ 14 cited
FedBoosting: Federated Learning with Gradient Protected Boosting for Text Recognition
Hanchi Ren, Jingjing Deng, Xianghua Xie +2
Typical machine learning approaches require centralized data for model training, which may not be possible where restrictions on data sharing are in place due to, for instance, pri…