Robust Federated Inference

Federated inference is different from federated learning. Federated learning emphasizes the aggregation of models trained on on-edge data; while federated inference focuses on that aggregate the results from distributedly deployed models. This paper focuses on robustness of this paradigm with theoretical formulation and analysis.