Image Classification on CIFAR-10 Cross-Silo (alpha=0.2)
68.87Top-1 AccuracyFEDSAM + CONST
Evaluation results
| Method | Links | |
|---|---|---|
| FEDSAM + CONSTModel=ResNet-182026.06 | 68.87 | |
| SCAFFOLD + CONSTModel=ResNet-182026.06 | 68.63 | |
| FEDAVG + CONSTModel=ResNet-182026.06 | 68.41 | |
| FEDPROX + CONSTModel=ResNet-182026.06 | 68.07 | |
| FEDDYN + CONSTModel=ResNet-182026.06 | 66 | |
| MOON + CONSTModel=ResNet-182026.06 | 62.52 | |
| FEDSAMModel=ResNet-182026.06 | 61.35 | |
| SCAFFOLDModel=ResNet-182026.06 | 59.3 | |
| FEDAVGModel=ResNet-182026.06 | 57.04 | |
| SCAFFOLD + CONSTModel=LeNet-52026.06 | 56.62 | |
| FEDPROX + CONSTModel=LeNet-52026.06 | 56.18 | |
| FEDDYN + CONSTModel=LeNet-52026.06 | 55.67 | |
| FEDDYNModel=ResNet-182026.06 | 55.09 | |
| FEDAVG + CONSTModel=LeNet-52026.06 | 54.79 | |
| FEDPROXModel=ResNet-182026.06 | 53.92 | |
| MOON + CONSTModel=LeNet-52026.06 | 52.88 | |
| MOONModel=ResNet-182026.06 | 51.51 | |
| FEDDYNModel=LeNet-52026.06 | 48.05 | |
| MOONModel=LeNet-52026.06 | 46.66 | |
| FEDAVGModel=LeNet-52026.06 | 46.42 | |
| SCAFFOLDModel=LeNet-52026.06 | 45.67 | |
| FEDPROXModel=LeNet-52026.06 | 45.27 |