Federated learning (FL) is a powerful distributed machine framework where server aggregates models trained by different clients without accessing their private data. Hierarchical FL, with client-edge-cloud aggregation hierarchy, can effectively leverage both the cloud server’s access to many clients’ data and edge servers’ closeness achieve high communication efficiency. Neural network quantiza...