Image Classification on ImageNet 64x64 (non-iid)
38.7AccuracyStandard
Evaluation Results
| Method | Links | |
|---|---|---|
| StandardBackbone=ResNet56, SFD/FedRolex ratio=1.0, Training rounds=40002023.05 | 38.7 | |
| SLTBackbone=ResNet56, SFD/FedRolex ratio=0.5, Training rounds=40002023.05 | 31.8 | |
| SLTBackbone=ResNet56, SFD/FedRolex ratio=0.25, Training rounds=40002023.05 | 29.7 | |
| Small modelBackbone=ResNet56, SFD/FedRolex ratio=0.5, Training rounds=40002023.05 | 27.3 | |
| SLTBackbone=ResNet56, SFD/FedRolex ratio=0.125, Training rounds=40002023.05 | 21.7 | |
| FedRolexBackbone=ResNet56, SFD/FedRolex ratio=0.5, Training rounds=40002023.05 | 18.4 | |
| Small modelBackbone=ResNet56, SFD/FedRolex ratio=0.25, Training rounds=40002023.05 | 16.2 | |
| FDBackbone=ResNet56, SFD/FedRolex ratio=0.5, Training rounds=40002023.05 | 15.7 | |
| FedRolexBackbone=ResNet56, SFD/FedRolex ratio=0.25, Training rounds=40002023.05 | 10.2 | |
| Small modelBackbone=ResNet56, SFD/FedRolex ratio=0.125, Training rounds=40002023.05 | 8.4 | |
| FedRolexBackbone=ResNet56, SFD/FedRolex ratio=0.125, Training rounds=40002023.05 | 2.8 | |
| FDBackbone=ResNet56, SFD/FedRolex ratio=0.125, Training rounds=40002023.05 | 0.1 | |
| FDBackbone=ResNet56, SFD/FedRolex ratio=0.25, Training rounds=40002023.05 | 0.1 |