Core Concepts
This paper introduces Serialized Random Smoothing (SRS), a novel method to efficiently certify the robustness of Deep Equilibrium Models (DEQs) by leveraging historical information in the randomized smoothing process, significantly reducing computational cost without sacrificing certified accuracy.
Gao, W., Hou, Z., Xu, H., & Liu, X. (2024). Certified Robustness for Deep Equilibrium Models via Serialized Random Smoothing. Advances in Neural Information Processing Systems, 38.
This paper addresses the computational challenges of certifying the robustness of Deep Equilibrium Models (DEQs) using randomized smoothing, aiming to improve efficiency without compromising accuracy.