2 papers
cs.LG2025
FedDAA: Dynamic Client Clustering for Concept Drift Adaptation in Federated Learning
Fu Peng, Ming Tang
In federated learning (FL), the data distribution of each client may change over time, introducing both temporal and spatial data heterogeneity, known as concept drift. Data hetero…
cs.LG2025
An Information-Theoretic Analysis for Federated Learning under Concept Drift
Fu Peng, Meng Zhang, Ming Tang
Recent studies in federated learning (FL) commonly train models on static datasets. However, real-world data often arrives as streams with shifting distributions, causing performan…