A practical approach to evaluating the adversarial distance for machine learning classifiers

Georg Siedel, Ekagra Gupta, Andrey Morozov

Robustness is critical for machine learning (ML) classifiers to ensure consistent performance in real-world applications where models may encounter corrupted or adversarial inputs.…