AAAI 2025technical0 citations
Dynamic Back-Substitution in Bound-Propagation-Based Neural Network Verification
Panagiotis Kouvaros, Benedikt Brückner, Patrick Henriksen, Alessio Lomuscio
Abstract
We improve the efficacy of bound-propagation-based neural network verification by reducing the computational effort required by state-of-the-art propagation methods without incurring any loss in precision. We propose a method that infers the stability of ReLU nodes at every step of the back-substitution process, thereby dynamically simplifying the coefficient matrix of the symbolic bounding equations. We develop a heuristic for the effective application of the method and discuss its evaluation on common benchmarks where we show significant improvements in bound propagation times.
BibTeX
@article{Kouvaros_Brückner_Henriksen_Lomuscio_2025, title={Dynamic Back-Substitution in Bound-Propagation-Based Neural Network Verification}, volume={39}, url={https://ojs.aaai.org/index.php/AAAI/article/view/34949}, DOI={10.1609/aaai.v39i26.34949}, abstractNote={We improve the efficacy of bound-propagation-based neural network verification by reducing the computational effort required by state-of-the-art propagation methods without incurring any loss in precision. We propose a method that infers the stability of ReLU nodes at every step of the back-substitution process, thereby dynamically simplifying the coefficient matrix of the symbolic bounding equations. We develop a heuristic for the effective application of the method and discuss its evaluation on common benchmarks where we show significant improvements in bound propagation times.}, number={26}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Kouvaros, Panagiotis and Brückner, Benedikt and Henriksen, Patrick and Lomuscio, Alessio}, year={2025}, month={Apr.}, pages={27383-27391} }