Image Classification on ImageNet-1K 64x64
41.6Top-1 AccuracyStandard
Evaluation Results
| Method | Links | |
|---|---|---|
| StandardBackbone=ResNet56, SFD/FedRolex ratio=1.0, Training rounds=40002023.05 | 41.6 | |
| SLTBackbone=ResNet56, SFD/FedRolex ratio=0.5, Training rounds=40002023.05 | 34.6 | |
| SLTBackbone=ResNet56, SFD/FedRolex ratio=0.25, Training rounds=40002023.05 | 31.2 | |
| Small modelBackbone=ResNet56, SFD/FedRolex ratio=0.5, Training rounds=40002023.05 | 30.3 | |
| SLTBackbone=ResNet56, SFD/FedRolex ratio=0.125, Training rounds=40002023.05 | 24.2 | |
| FedRolexBackbone=ResNet56, SFD/FedRolex ratio=0.5, Training rounds=40002023.05 | 21.3 | |
| Full Dataset2022.06 | 19.8 | |
| Small modelBackbone=ResNet56, SFD/FedRolex ratio=0.25, Training rounds=40002023.05 | 18.4 | |
| FDBackbone=ResNet56, SFD/FedRolex ratio=0.5, Training rounds=40002023.05 | 16.8 | |
| FedRolexBackbone=ResNet56, SFD/FedRolex ratio=0.25, Training rounds=40002023.05 | 11.4 | |
| FRePoImg/Cls=22022.06 | 9.7 | |
| FRePoImg/Cls=22022.06 | 9.7 | |
| Small modelBackbone=ResNet56, SFD/FedRolex ratio=0.125, Training rounds=40002023.05 | 8.9 | |
| FRePoImg/Cls=12022.06 | 7.5 | |
| FRePoImg/Cls=12022.06 | 7.5 | |
| FDBackbone=ResNet56, SFD/FedRolex ratio=0.25, Training rounds=40002023.05 | 6.2 | |
| FedRolexBackbone=ResNet56, SFD/FedRolex ratio=0.125, Training rounds=40002023.05 | 3.4 | |
| Random SubsetImg/Cls=22022.06 | 1.4 | |
| Random SubsetImg/Cls=22022.06 | 1.4 | |
| Random SubsetImg/Cls=12022.06 | 1.1 | |
| Random SubsetImg/Cls=12022.06 | 1.1 | |
| FDBackbone=ResNet56, SFD/FedRolex ratio=0.125, Training rounds=40002023.05 | 0.3 |