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Which defense technique trains ML models with adversarial examples to improve robustness?
- Adversarial Training
- Defensive Distillation
- Randomized Smoothing
- All of these
Answer: All of these
Adversarial defenses: adversarial training includes perturbed examples, defensive distillation smooths outputs, randomized smoothing adds noise. All improve robustness against adversarial attacks.