Image Classification on EMNIST Letters (test)
95.96AccuracyWaveMix
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| WaveMixAugmentation=TrivialAugment2022.05 | 95.96 | — | — | |
| Previous SOTA [73]2022.05 | 95.88 | — | — | |
| VGG-5 (Spinal FC)Size of Fully Connected Layer=4HL, 128 Neurons Per Layer, Epoch=200, Parameters=3.630M2020.07 | 95.79 | 95.88 | 0.5 | |
| VGG-5Size of Fully Connected Layer=1HL, 512 Neurons, Epoch=200, Parameters=3.646M2020.07 | 95.71 | 95.86 | — | |
| CNN (Spinal FC)Size of Fully Connected Layer=6HL, 10 Neurons Per Layer, Epoch=8, Parameters=16.05k2020.07 | 90.02 | 90.23 | 21.4 | |
| CNN (Spinal FC)Size of Fully Connected Layer=6HL, 8 Neurons Per Layer, Epoch=8, Parameters=13.82k2020.07 | 89.88 | 90.07 | 20.11 | |
| CNNSize of Fully Connected Layer=1HL, 50 Neurons, Epoch=8, Parameters=21.84k2020.07 | 87.29 | 87.57 | — | |
| FedCILLocal training iteration (T)=400, Global communication round (R)=200, Mini-batch size (B)=32, Backbone=3-layer CNN, Optimizer=Adam, Learning rate=1e-42023.02 | 78.15 | — | — | |
| FedProx+ACGAN ReplayLocal training iteration (T)=400, Global communication round (R)=200, Mini-batch size (B)=32, Backbone=3-layer CNN, Optimizer=Adam, Learning rate=1e-42023.02 | 73.91 | — | — | |
| FedAvg+ACGAN ReplayLocal training iteration (T)=400, Global communication round (R)=200, Mini-batch size (B)=32, Backbone=3-layer CNN, Optimizer=Adam, Learning rate=1e-42023.02 | 73.85 | — | — | |
| FedAvg+DGRLocal training iteration (T)=400, Global communication round (R)=200, Mini-batch size (B)=32, Backbone=3-layer CNN, Optimizer=Adam, Learning rate=1e-42023.02 | 71.92 | — | — | |
| FedProx+DGRLocal training iteration (T)=400, Global communication round (R)=200, Mini-batch size (B)=32, Backbone=3-layer CNN, Optimizer=Adam, Learning rate=1e-42023.02 | 71.83 | — | — | |
| FedLwF-2TLocal training iteration (T)=400, Global communication round (R)=200, Mini-batch size (B)=32, Backbone=3-layer CNN, Optimizer=Adam, Learning rate=1e-42023.02 | 23.91 | — | — | |
| FedProxLocal training iteration (T)=400, Global communication round (R)=200, Mini-batch size (B)=32, Backbone=3-layer CNN, Optimizer=Adam, Learning rate=1e-42023.02 | 19.69 | — | — | |
| FedAvgLocal training iteration (T)=400, Global communication round (R)=200, Mini-batch size (B)=32, Backbone=3-layer CNN, Optimizer=Adam, Learning rate=1e-42023.02 | 19.36 | — | — |