Image Classification on CIFAR-100 (test) (Test Accuracy)
49.36Test AccuracySpecGradFilter
Evaluation Results
| Method | Links | |
|---|---|---|
| SpecGradFilteralpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 49.36 | |
| FedDynalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 46.45 | |
| FedCMalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 43.86 | |
| SCAFFOLDalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 43.31 | |
| FedAvgalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 40.9 | |
| FedProxalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 40.56 | |
| FedAWAalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 40.32 | |
| FedDiscoalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 40 | |
| FedLWSalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 39.73 | |
| FedSAMalpha=100, Backbone=ResNet-20, Clients=100, Client Participation Rate=0.1, Communication Rounds=3002026.07 | 39.5 |