Image Classification on Tiny-ImageNet (beta=0.5)
73.89AccuracyGGEUR
Evaluation Results
| Method | Links | |
|---|---|---|
| GGEURBackbone=CLIP+MLP, Federated Learning Algorithm=FedAvg2025.03 | 73.89 | |
| FEDGEN (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FEDGEN2025.03 | 72.37 | |
| FedMix (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedMix2025.03 | 70.89 | |
| FedCLIPFederated Learning Algorithm=FedCLIP2025.03 | 70.41 | |
| FedFA (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedFA2025.03 | 70.41 | |
| FedAvg (CLIP+MLP)Backbone=CLIP+MLP, Federated Learning Algorithm=FedAvg2025.03 | 70.08 | |
| FedTPGFederated Learning Algorithm=FedTPG2025.03 | 67.63 | |
| Zero-Shot CLIPBackbone=CLIP, Mode=Zero-Shot2025.03 | 63.67 |