2 papers
cs.LG2025
AMSFL: Adaptive Multi-Step Federated Learning via Gradient Difference-Based Error Modeling
Ganglou Xu
Federated learning faces critical challenges in balancing communication efficiency and model accuracy. One key issue lies in the approximation of update errors without incurring hi…
cs.CV2025
FNBench: Benchmarking Robust Federated Learning against Noisy Labels
Xuefeng Jiang, Jia Li, Nannan Wu +7
Robustness to label noise within data is a significant challenge in federated learning (FL). From the data-centric perspective, the data quality of distributed datasets can not be…