Image Classification on CIFAR-10 label shift (test)
65.96Top-1 AccuracyLSS
Evaluation results
| Method | Links | ||
|---|---|---|---|
| LSSBackbone=ResNet-18, Pre-trained=ImageNet, Memory=4x2024.10 | 65.96 | 75.16 | |
| DiWABackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 61.32 | 68.05 | |
| SoupsBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 61 | 67.63 | |
| SWADBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 60.54 | 67.65 | |
| FedBABUBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 60.14 | 67.16 | |
| SWABackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 59.07 | 67.45 | |
| MOONBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 58.96 | 67.04 | |
| FedAvgBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 58.34 | 66.74 | |
| FedRepBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 57.73 | 66.23 | |
| FedBNBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 57.04 | 64.51 | |
| FedProxBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 56.74 | 63.21 | |
| FedFomoBackbone=ResNet-18, Pre-trained=ImageNet2024.10 | 55.01 | 62.69 |