2 papers
cs.DC2024
Rethinking Personalized Federated Learning with Clustering-based Dynamic Graph Propagation
Jiaqi Wang, Yuzhong Chen, Yuhang Wu +3
Most existing personalized federated learning approaches are based on intricate designs, which often require complex implementation and tuning. In order to address this limitation,…
cs.CR2023
Privacy-Preserving Financial Anomaly Detection via Federated Learning & Multi-Party Computation
Sunpreet Arora, Andrew Beams, Panagiotis Chatzigiannis +9
One of the main goals of financial institutions (FIs) today is combating fraud and financial crime. To this end, FIs use sophisticated machine-learning models trained using data co…