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That's not the interesting part, the interesting part is: What is even more shocking is that the adversarial examples seem to have some sort of universality. T
by streptomycin 12y ago
That's not the interesting part, the interesting part is:
What is even more shocking is that the adversarial examples seem to have some sort of universality. That is a large fraction were misclassified by different network architectures trained on the same data and by networks trained on a different data set.
- ivanca 12y agoYeah, It is the interesting part. Because with sufficiently large inputs (even from different sources) the networks are going to be looking for the same patterns.
- streptomycin 12y agoBut why would different structures of networks fit to different data result in exactly the same type of "overfitting"?