Image Classification on CIFAR-100 (beta=0.1)
77.7AccuracyGGEUR
Evaluation results
| Method | Links | |
|---|---|---|
| GGEURBackbone=CLIP+MLP, Federated Learning Algorithm=FedAvg2025.03 | 77.7 | |
| FedFA (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedFA2025.03 | 74.68 | |
| FedMix (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedMix2025.03 | 73.85 | |
| FEDGEN (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FEDGEN2025.03 | 73.15 | |
| FedCLIPFederated Learning Algorithm=FedCLIP2025.03 | 70.64 | |
| FedTPGFederated Learning Algorithm=FedTPG2025.03 | 68.63 | |
| FedAvg (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedAvg2025.03 | 68.22 |