1 citations · 1 across the 1 of their papers we have counts for
3 papers
cs.LG2023
ALI-DPFL: Differentially Private Federated Learning with Adaptive Local Iterations
Xinpeng Ling, Jie Fu, Kuncan Wang +2
Federated Learning (FL) is a distributed machine learning technique that allows model training among multiple devices or organizations by sharing training parameters instead of raw…
cs.CV2023
NIPD: A Federated Learning Person Detection Benchmark Based on Real-World Non-IID Data
Kangning Yin, Zhen Ding, Zhihua Dong +5
Federated learning (FL), a privacy-preserving distributed machine learning, has been rapidly applied in wireless communication networks. FL enables Internet of Things (IoT) clients…
cs.LG2022★ 1 cited
Adap DP-FL: Differentially Private Federated Learning with Adaptive Noise
Jie Fu, Zhili Chen, Xiao Han
Federated learning seeks to address the issue of isolated data islands by making clients disclose only their local training models. However, it was demonstrated that private inform…