Personalized Federated Learning On Cifar 100
Metrics
ACC@1-100Clients
ACC@1-10Clients
ACC@1-500
ACC@1-50Clients
Results
Performance results of various models on this benchmark
Model Name | ACC@1-100Clients | ACC@1-10Clients | ACC@1-500 | ACC@1-50Clients | Paper Title | Repository |
|---|---|---|---|---|---|---|
| pFedHN-PC | 52.40 | 68.15 | 34.1 | 60.17 | Personalized Federated Learning using Hypernetworks | |
| pFedGP-IP-compute | 59.8 | - | 49.2 | 61.2 | Personalized Federated Learning with Gaussian Processes | |
| pFedGP-IP-data | 58.5 | - | 55.7 | 60.2 | Personalized Federated Learning with Gaussian Processes | |
| pFedGP | 61.3 | - | 50.6 | 63.3 | Personalized Federated Learning with Gaussian Processes | |
| SuPerFed-MM | - | - | - | - | Connecting Low-Loss Subspace for Personalized Federated Learning | |
| pFedHN | 53.24 | 65.74 | - | 59.46 | Personalized Federated Learning using Hypernetworks | |
| SuPerFed-LM | - | - | - | - | Connecting Low-Loss Subspace for Personalized Federated Learning |
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