Image Classification on CIFAR-10 30% symmetric noise (test)
82.26AccuracyDCQ
Evaluation Results
| Method | Links | |
|---|---|---|
| DCQBackbone=ResNet-18, Pruning Ratio=80%2026.02 | 82.26 | |
| CCSBackbone=ResNet-18, Pruning Ratio=80%2026.02 | 78.51 | |
| TDDSBackbone=ResNet-18, Pruning Ratio=80%2026.02 | 77.44 | |
| RandomBackbone=ResNet-18, Pruning Ratio=80%2026.02 | 76.51 | |
| DCQBackbone=ResNet-18, Pruning Ratio=87.5%2026.02 | 73.44 | |
| CCSBackbone=ResNet-18, Pruning Ratio=87.5%2026.02 | 69.35 | |
| DCQBackbone=ResNet-18, Pruning Ratio=92%2026.02 | 68.34 | |
| TDDSBackbone=ResNet-18, Pruning Ratio=87.5%2026.02 | 67.99 | |
| RandomBackbone=ResNet-18, Pruning Ratio=87.5%2026.02 | 67.18 | |
| CCSBackbone=ResNet-18, Pruning Ratio=92%2026.02 | 64.16 | |
| TDDSBackbone=ResNet-18, Pruning Ratio=92%2026.02 | 63.66 | |
| RandomBackbone=ResNet-18, Pruning Ratio=92%2026.02 | 62.05 | |
| DCQBackbone=ResNet-18, Pruning Ratio=96%2026.02 | 59.17 | |
| CCSBackbone=ResNet-18, Pruning Ratio=96%2026.02 | 51.28 | |
| TDDSBackbone=ResNet-18, Pruning Ratio=96%2026.02 | 50.85 | |
| RandomBackbone=ResNet-18, Pruning Ratio=96%2026.02 | 49.36 | |
| RACTBackbone=CNN, Noise level=30%, Noise type=symmetric, Seeds=3-52026.01 | 47.36 | |
| CoTBackbone=CNN, Noise level=30%, Noise type=symmetric, Seeds=12026.01 | 47 | |
| CEBackbone=CNN, Noise level=30%, Noise type=symmetric, Seeds=12026.01 | 46.71 | |
| LSBackbone=CNN, Noise level=30%, Noise type=symmetric, Seeds=12026.01 | 46.51 | |
| DivideMixBackbone=CNN, Noise level=30%, Noise type=symmetric, Seeds=22026.01 | 38.63 |