Jakob Spiegelberg

Guaranteeing Robustness Against Real-World Perturbations In Time Series Classification Using Conformalized Randomized Smoothing

Certifying the robustness of machine learning models against domain shifts and input space perturbations is crucial for many applications, where high risk decisions are based on the model’s predictions. Techniques such as randomized smoothing have partially addressed this issues with a focus on adve…