Image Classification on CIFAR-100 Cross-Silo, alpha=0.5
39.61Top-1 AccuracyFEDSAM + CONST
Evaluation results
| Method | Links | |
|---|---|---|
| FEDSAM + CONSTModel=ResNet-182026.06 | 39.61 | |
| SCAFFOLD + CONSTModel=ResNet-182026.06 | 38.93 | |
| FEDSAMModel=ResNet-182026.06 | 38.43 | |
| FEDDYN + CONSTModel=ResNet-182026.06 | 37.22 | |
| SCAFFOLDModel=ResNet-182026.06 | 37.18 | |
| FEDAVG + CONSTModel=ResNet-182026.06 | 36.82 | |
| MOON + CONSTModel=ResNet-182026.06 | 36.8 | |
| FEDPROX + CONSTModel=ResNet-182026.06 | 36.56 | |
| MOONModel=ResNet-182026.06 | 35.19 | |
| FEDDYNModel=ResNet-182026.06 | 35.07 | |
| FEDPROXModel=ResNet-182026.06 | 34.11 | |
| FEDAVGModel=ResNet-182026.06 | 33.51 | |
| FEDDYN + CONSTModel=LeNet-52026.06 | 27.14 | |
| FEDAVG + CONSTModel=LeNet-52026.06 | 26.86 | |
| FEDPROX + CONSTModel=LeNet-52026.06 | 26.78 | |
| MOON + CONSTModel=LeNet-52026.06 | 26.76 | |
| SCAFFOLD + CONSTModel=LeNet-52026.06 | 26.74 | |
| MOONModel=LeNet-52026.06 | 18.72 | |
| FEDPROXModel=LeNet-52026.06 | 18.42 | |
| SCAFFOLDModel=LeNet-52026.06 | 17.66 | |
| FEDAVGModel=LeNet-52026.06 | 17.46 | |
| FEDDYNModel=LeNet-52026.06 | 16.79 |