Continual Learning on {MNIST, SVHN, notMNIST, FashionMNIST, CIFAR-10} (test)
90.56AADECODE
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| DECODEBackbone=ViT, Optimization Epochs=252024.11 | 90.56 | — | 0.05 | |
| DualpromptBackbone=ViT, Optimization Epochs=252024.11 | 88.08 | — | 2.21 | |
| PEFT Ensemble (FiLM)Differential Privacy budget (epsilon)=8, Privacy parameter (delta)=1e-5, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 87.83 | 3 | — | |
| DER++Memory Buffer Size=500, Backbone=ViT, Optimization Epochs=252024.11 | 84.88 | — | 10.46 | |
| Coda-PBackbone=ViT, Optimization Epochs=252024.11 | 84.82 | — | 13.24 | |
| ERMemory Buffer Size=500, Backbone=ViT, Optimization Epochs=252024.11 | 84.26 | — | 12.85 | |
| F2PBackbone=ViT, Optimization Epochs=252024.11 | 81.14 | — | 4.64 | |
| PEFT Ensemble (FiLM)Differential Privacy budget (epsilon)=1, Privacy parameter (delta)=1e-5, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 79.69 | 5 | — | |
| PEFT Ensemble (FiLM)Differential Privacy budget (epsilon)=non-DP, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 65.75 | 14 | — | |
| Cosine classifierDifferential Privacy budget (epsilon)=non-DP, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 59.87 | 0 | — | |
| Cosine classifierDifferential Privacy budget (epsilon)=8, Privacy parameter (delta)=1e-5, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 59.78 | 0 | — | |
| Cosine classifierDifferential Privacy budget (epsilon)=1, Privacy parameter (delta)=1e-5, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 58.54 | 1 | — | |
| EWCBackbone=ViT, Optimization Epochs=252024.11 | 50.93 | — | 34.94 | |
| LwFBackbone=ViT, Optimization Epochs=252024.11 | 47.91 | — | 38.01 | |
| NaiveDifferential Privacy budget (epsilon)=8, Privacy parameter (delta)=1e-5, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 17.56 | 90 | — | |
| NaiveDifferential Privacy budget (epsilon)=1, Privacy parameter (delta)=1e-5, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 15.93 | 85 | — | |
| NaiveDifferential Privacy budget (epsilon)=non-DP, Backbone=ViT-B, Pre-training dataset=ImageNet-21k2024.11 | 13.15 | 79 | — |