Image Classification on CIFAR10 IID (Accuracy and Binarized Accuracy)
0.9086AccuracyFedAvg
Evaluation results
| Method | Links | ||
|---|---|---|---|
| FedAvgModel=ResNet10, Nc=100, FLOPs=4.40 × 10^8, Memory (MB)=19.61702026.03 | 0.9086 | 0.172 | |
| FedBNNModel=ResNet10, Nc=100, FLOPs=1.11 × 10^7, Memory (MB)=0.61302026.03 | 0.8995 | 0.8995 | |
| FedBATModel=ResNet10, Nc=100, FLOPs=4.40 × 10^8, Memory (MB)=19.61702026.03 | 0.8938 | 0.1362 | |
| FedMUDModel=ResNet10, Nc=100, FLOPs=4.40 × 10^8, Memory (MB)=19.61702026.03 | 0.8874 | 0.1554 | |
| FedBNNModel=ConvNeXt-Tiny, Nc=100, FLOPs=6.07 × 10^7, Memory (MB)=3.48872026.03 | 0.7208 | 0.7208 | |
| FedBATModel=ConvNeXt-Tiny, Nc=100, FLOPs=2.98 × 10^9, Memory (MB)=111.6402026.03 | 0.6604 | 0.149 | |
| FedAvgModel=ConvNeXt-Tiny, Nc=100, FLOPs=2.98 × 10^9, Memory (MB)=111.6402026.03 | 0.6522 | 0.1804 | |
| FedMUDModel=ConvNeXt-Tiny, Nc=100, FLOPs=2.98 × 10^9, Memory (MB)=111.6402026.03 | 0.5392 | 0.4046 |