Image Classification on CIFAR-10 (Accuracy and Iterations)
94.56AccuracyCBS-10-3
Evaluation results
| Method | Links | ||
|---|---|---|---|
| CBS-10-3Model Architecture=WResNet (C2), Strategy=CBS-10-32018.12 | 94.56 | 45,000 | |
| BaselineModel Architecture=WResNet (C2), Strategy=Baseline2018.12 | 94.53 | 78,000 | |
| CBS-15Model Architecture=WResNet (C2), Strategy=CBS-152018.12 | 94.46 | 40,000 | |
| CBS-5-3Model Architecture=WResNet (C2), Strategy=CBS-5-32018.12 | 94.44 | 45,000 | |
| CBS-5-3-AModel Architecture=WResNet (C2), Strategy=CBS-5-3-A2018.12 | 94.34 | 33,000 | |
| BaselineModel Architecture=ResNet18 (C3), Strategy=Baseline2018.12 | 92.71 | 63,000 | |
| CBS-15-2Model Architecture=ResNet18 (C3), Strategy=CBS-15-22018.12 | 92.58 | 48,000 | |
| CBS-10Model Architecture=ResNet18 (C3), Strategy=CBS-102018.12 | 92.47 | 32,000 | |
| CBS-5-3Model Architecture=ResNet18 (C3), Strategy=CBS-5-32018.12 | 92.45 | 37,000 | |
| CBS-15-2-AModel Architecture=ResNet18 (C3), Strategy=CBS-15-2-A2018.12 | 92.27 | 39,000 | |
| CBS-5-3Model Architecture=AlexNet-like (C1), Strategy=CBS-5-32018.12 | 87.03 | 20,000 | |
| BaselineModel Architecture=AlexNet-like (C1), Strategy=Baseline2018.12 | 86.94 | 35,000 | |
| CBS-15-2Model Architecture=AlexNet-like (C1), Strategy=CBS-15-22018.12 | 86.87 | 26,000 | |
| CBS-10-3Model Architecture=AlexNet-like (C1), Strategy=CBS-10-32018.12 | 86.83 | 20,000 | |
| CBS-5-3-AModel Architecture=AlexNet-like (C1), Strategy=CBS-5-3-A2018.12 | 86.75 | 15,000 |