Lipschitz Constant

The Lipschitz constant quantifies the smoothness or sensitivity of a function, particularly relevant in analyzing the robustness and stability of deep neural networks (DNNs). Current research focuses on efficiently estimating Lipschitz constants for various DNN architectures, including convolutional neural networks (CNNs) and Transformers, often employing compositional methods or linear bound propagation to handle the computational challenges posed by large networks. Accurate Lipschitz constant estimation is crucial for certifying the robustness of DNNs to adversarial attacks, improving generalization performance, and enabling the development of provably stable and reliable AI systems across diverse applications.