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Is the assertion that adversarial ML is a subset of correctness widely considered canonical? That appears counterintuitive because so many ML techniques seem (
by rlucas 10y ago
Is the assertion that adversarial ML is a subset of correctness widely considered canonical?
That appears counterintuitive because so many ML techniques seem (for lack of a technically defined term) tautological. For example, a big hairy random forest classifier maybe can be gamed in certain cases, but it is not "correct?" After all, it is its own definition.
- argonaut 10y agoYes. I'm not sure what point you're trying to make about tautology. Adversarial ML examples are clearly errors if they were part of the test set, and part of "correctness" is reducing the error rate (correct model, correct parameters, etc.).