Permutation Invariant Image Classification on MNIST (test)
0.57Error RateLadder, full
Evaluation Results
| Method | Links | |
|---|---|---|
| Ladder, fullNumber of used labels=All2015.07 | 0.57 | |
| Ladder, only bottom-level costNumber of used labels=All2015.07 | 0.59 | |
| Virtual AdversarialNumber of used labels=All2015.07 | 0.64 | |
| AdversarialNumber of used labels=All2015.07 | 0.78 | |
| Γ-modelNumber of used labels=All2015.07 | 0.78 | |
| DBM, DropoutNumber of used labels=All2015.07 | 0.79 | |
| Baseline: MLP, BN, Gaussian noiseNumber of used labels=All2015.07 | 0.8 | |
| MTCNumber of used labels=All2015.07 | 0.81 | |
| Ladder, fullNumber of used labels=10002015.07 | 0.84 | |
| Ladder, only bottom-level costNumber of used labels=10002015.07 | 0.9 | |
| DGNNumber of used labels=All2015.07 | 0.96 | |
| Ladder, fullNumber of used labels=1002015.07 | 1.06 | |
| Ladder, only bottom-level costNumber of used labels=1002015.07 | 1.09 | |
| AtlasRBFNumber of used labels=All2015.07 | 1.31 | |
| Virtual AdversarialNumber of used labels=10002015.07 | 1.32 | |
| Transductive SVMNumber of used labels=All2015.07 | 1.4 | |
| Semi-sup. EmbeddingNumber of used labels=All2015.07 | 1.5 | |
| Γ-modelNumber of used labels=10002015.07 | 1.53 | |
| Virtual AdversarialNumber of used labels=1002015.07 | 2.12 | |
| DGNNumber of used labels=10002015.07 | 2.4 | |
| Γ-modelNumber of used labels=1002015.07 | 3.06 | |
| DGNNumber of used labels=1002015.07 | 3.33 | |
| Pseudo-labelNumber of used labels=10002015.07 | 3.46 | |
| MTCNumber of used labels=10002015.07 | 3.64 | |
| AtlasRBFNumber of used labels=10002015.07 | 3.68 | |
| Transductive SVMNumber of used labels=10002015.07 | 5.38 | |
| Baseline: MLP, BN, Gaussian noiseNumber of used labels=10002015.07 | 5.7 | |
| Semi-sup. EmbeddingNumber of used labels=10002015.07 | 5.73 | |
| AtlasRBFNumber of used labels=1002015.07 | 8.1 | |
| Pseudo-labelNumber of used labels=1002015.07 | 10.49 | |
| MTCNumber of used labels=1002015.07 | 12.03 | |
| Transductive SVMNumber of used labels=1002015.07 | 16.81 | |
| Semi-sup. EmbeddingNumber of used labels=1002015.07 | 16.86 | |
| Baseline: MLP, BN, Gaussian noiseNumber of used labels=1002015.07 | 21.74 |