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.

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.