Privacy-Preserving Federated Learning for Container Kubernetes Orchestration in Uganda: Robustness Under Distribution Shift and Sparse Labels
Federated learning offers a compelling architecture for training machine learning models across distributed Kubernetes clusters without centralising sensitive data, yet its practical deployment in resource-constrained settings such as Uganda confronts two interrelated obstacles that current literature treats in isolati...