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Not necessarily. Adversarial examples have been shown to, for instance, be transferable across different networks with different hyperparameters (e.g., number o
by haraldurt 9y ago
Not necessarily. Adversarial examples have been shown to, for instance, be transferable across different networks with different hyperparameters (e.g., number of layers) trained on disjoint subsets of a training set [0, section 4.2]. There are more references from the paper linked by the OP.
[0] https://arxiv.org/abs/1312.6199 https://arxiv.org/abs/1312.6199
- naveen99 9y agoThanks. I wonder if adversarial training helps prevent overfitting too. Could you use adversarial training to beat alphago ?
- yorwba 9y agoYou could not, because AlphaGo is not a classifier (so it isn't well-defined what an adversarial example is) and the input space is discrete (Go board state) and you can't do ε-small perturbations (two different states differ by at least one stone).