2 papers
cs.LG2026
FedCausal-Dyn: A Causal-Dynamic Paradigm for Federated Learning under Dynamic Feature Drift
Kaijie Chen, Alex Johnson, Maria Garcia +2
This paper addresses the challenging problem of dynamic feature drift in federated learning, where data distributions evolve across clients and over time -- a common scenario in re…
cs.LG2026
Efficient Personalized Federated PCA with Manifold Optimization for IoT Anomaly Detection
Xianchao Xiu, Chenyi Huang, Wei Zhang +1
Internet of things (IoT) networks face increasing security threats due to their distributed nature and resource constraints. Although federated learning (FL) has gained prominence…