Integrating Particle Swarm Dynamics into Federated Learning: A Promising Hybrid to Counter Client Drift under Non-IID Conditions
Federated learning (FL) enables distributed model training without centralizing raw data, making it attractive for privacy-sensitive Internet of Things (IoT) environments.However, conventional FL algorithms suffer from slow convergence and degraded performance under statistically heterogeneous (non-IID) data distributi...