Image Classification on CIFAR-100 (beta=0.3)
81.65AccuracyGGEUR
Evaluation results
| Method | Links | |
|---|---|---|
| GGEURBackbone=CLIP+MLP, Federated Learning Algorithm=FedAvg2025.03 | 81.65 | |
| FedMix (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedMix2025.03 | 79.62 | |
| FedFA (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedFA2025.03 | 79.31 | |
| FEDGEN (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FEDGEN2025.03 | 78.97 | |
| FedAvg (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedAvg2025.03 | 77.68 | |
| FedCLIPFederated Learning Algorithm=FedCLIP2025.03 | 71.2 | |
| FedTPGFederated Learning Algorithm=FedTPG2025.03 | 70.95 |