Does Order Matter : Connecting The Law of Robustness to Robust Generalization
Researchers have established a connection between the Law of Robustness and robust generalization error in machine learning. They proved that the order of the Lipschitz bound remains consistent when analyzing the global Rademacher complexity of robust loss classes. Furthermore, at a local scale for functions with small empirical error, the Lipschitz bound's order is shown to change based on the perturbation radius and a localized concentration term. AI
IMPACT Establishes theoretical links between robustness and generalization, potentially guiding future model development for improved reliability.