Image Classification on CIFAR-10 LeNet-5 (test)
49Communication RoundsGradMA
Evaluation results
| Method | Links | |
|---|---|---|
| GradMAomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 49 | |
| GradMA-Somega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 56 | |
| Feddynomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 66 | |
| FedMLBMomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 77 | |
| FedMLBomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 78 | |
| MOONMomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 78 | |
| FedAvgMomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 79 | |
| MIFAMomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 80 | |
| GradMA-Somega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 83 | |
| MIFAomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 89 | |
| MimeLiteomega=0.1, S=10, target accuracy=55%, backbone=LeNet-5, communication load=2x per round2023.02 | 92 | |
| MOONMomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 95 | |
| MOONomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 96 | |
| FedProxMomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 96 | |
| Feddynomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 96 | |
| FedProxMomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 97 | |
| GradMA-Somega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 101 | |
| GradMAomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 105 | |
| MimeLiteomega=1.0, S=10, target accuracy=50%, backbone=LeNet-5, communication load=2x per round2023.02 | 113 | |
| FedAvgomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 117 | |
| FedProxomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 117 | |
| MOONomega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 117 | |
| GradMAomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 130 | |
| FedProxomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 141 | |
| MIFAMomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 152 | |
| MIFAomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 156 | |
| GradMA-Womega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 168 | |
| GradMA-Womega=1.0, S=10, target accuracy=50%, backbone=LeNet-52023.02 | 172 | |
| FedAvgMomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 175 | |
| FedAvgomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 177 | |
| FedMLBMomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 185 | |
| FedMLBomega=0.1, S=10, target accuracy=55%, backbone=LeNet-52023.02 | 245 | |
| MIFAMomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 325 | |
| MimeLiteomega=0.01, S=10, target accuracy=45%, backbone=LeNet-5, communication load=2x per round2023.02 | 385 | |
| MIFAomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 393 | |
| GradMA-Womega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 582 | |
| FedAvgMomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 605 | |
| MOONomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 616 | |
| FedProxMomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 631 | |
| FedMLBMomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 653 | |
| FedMLBomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 694 | |
| FedProxomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 766 | |
| MOONMomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 766 | |
| FedAvgomega=0.01, S=10, target accuracy=45%, backbone=LeNet-52023.02 | 882 |