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Adversarial Examples and Adversarial Training
Attacking Linear Models
Gradient-based adversarial examples
Misclassification Errors
Replacing the last layer of the model
Misclassification
Adversarial Examples Transfer Between Machine Learning Models
The Universal Approximator Theorem
Conclusion
Q&A: How is the dimension of the adversarial subspace related to the dimension of the input?
Intro
Incentives to manipulate model behaviour
Generalized label-flipping attack
Trade-off between accuracy and robustness
What is certified robustness?
Robustness and differential privacy
Analytic relationship between class probabilities and certification radius
Advantage of noise-based mechanisms
Adversarial Examples in the Real World
Conclusion
Adversarial Examples
Other Motivations for Researching Adversarial Robustness
Adversarial Example for a Simple Binary Classifier
Adversarial Attack That Conforms to the Lp Threat Model
Pseudo Code
Adversarial Attacks and Adversarial Training
Testing the Robustness of Models
Broader Threat Model
Factors That Influence an Adversary's Strength
Robustness Guarantees