Privacy-Preserving Federated Learning for Forced Displacement Broader Than Conflict in Uganda: Robustness Under Distribution Shift and Sparse Labels
Forced displacement in Uganda extends well beyond conflict-driven flight, encompassing disaster-induced mobility, climate pressures and economic relocation, yet machine learning systems designed to support displaced populations typically assume stable data distributions and abundant labelled examples. We introduce a fe...