developer.nvidia.com
2026-06-10
NVIDIA Developer
Federated learning (FL) research often begins with a deceptively simple question: What should we try next? A new aggregation rule, a FedProx coefficient, a server optimizer setting, a SCAFFOLD variant, or a model architecture tweak may all look promising before an experiment starts.
After the run finishes, the harder questions begin: Did the change actually improve the metric? Was the comparison