Image Classification on CIFAR-10 Cross-Silo (alpha=0.5)
75.09Top-1 AccuracySCAFFOLD + CONST
Evaluation results
| Method | Links | |
|---|---|---|
| SCAFFOLD + CONSTModel=ResNet-182026.06 | 75.09 | |
| FEDSAM + CONSTModel=ResNet-182026.06 | 72.64 | |
| FEDAVG + CONSTModel=ResNet-182026.06 | 72.44 | |
| FEDPROX + CONSTModel=ResNet-182026.06 | 71.96 | |
| MOON + CONSTModel=ResNet-182026.06 | 71.84 | |
| FEDDYN + CONSTModel=ResNet-182026.06 | 71.76 | |
| FEDSAMModel=ResNet-182026.06 | 69.45 | |
| MOONModel=ResNet-182026.06 | 68.45 | |
| FEDDYNModel=ResNet-182026.06 | 65.5 | |
| FEDPROXModel=ResNet-182026.06 | 64.51 | |
| SCAFFOLDModel=ResNet-182026.06 | 64.5 | |
| FEDAVGModel=ResNet-182026.06 | 64.25 | |
| SCAFFOLD + CONSTModel=LeNet-52026.06 | 63.03 | |
| FEDPROX + CONSTModel=LeNet-52026.06 | 60.7 | |
| MOON + CONSTModel=LeNet-52026.06 | 59.86 | |
| FEDDYN + CONSTModel=LeNet-52026.06 | 59.76 | |
| FEDAVG + CONSTModel=LeNet-52026.06 | 59.66 | |
| MOONModel=LeNet-52026.06 | 55.79 | |
| FEDPROXModel=LeNet-52026.06 | 55.15 | |
| FEDAVGModel=LeNet-52026.06 | 53.12 | |
| SCAFFOLDModel=LeNet-52026.06 | 52.74 | |
| FEDDYNModel=LeNet-52026.06 | 51.05 |