Research map / Learning theory and algorithms / Prediction and decision losses
Robust Implicit Networks via Non-Euclidean Contractions
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use NEMON instead of implicit deep learning | MNIST image classification · MNIST | best accuracy: 0.9721 -> 0.9772 | Helped |
| Use NEMON instead of MON | MNIST image classification · MNIST | best accuracy: 0.9762 -> 0.9772 | Helped |
| Add input-output Lipschitz regularization (ablation) | NEMON · MNIST | input-output Lipschitz constant: two order of magnitude decrease | Helped |
| Increase the input-output Lipschitz regularization parameter (ablation) | NEMON · MNIST continuous image inversion attack | robustness | Helped |
| Use NEMON instead of implicit deep learning or MON | Image classification under continuous image inversion attack · MNIST | robustness | Helped |
| Use NEMON instead of MON | Image classification under ℓ∞-bounded perturbations · CIFAR-10 | robustness | Helped |
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