Author

Christoph Hertrich

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#machine learning Sep 2025

Parameterized Hardness of Zonotope Containment and Neural Network Verification

It is proved that, for all $\ell\ge 2$, deciding positivity (and thus surjectivity) of a function computed by an $\ell$-layer ReLU network is W[$\ell-1$]-hard when parameterized by the input dimension $d$.

Vincent Froese, Moritz Grillo, Christoph Hertrich et al. · arXiv.org · 9 citations · ⚡2

Preprint Aug 2026

Parameterized Complexity of $L_p$-Lipschitz Constants for Input Convex Neural Networks and $L_p$-Norm Maximization over Zonotopes

These results resolve the corresponding questions regarding the parameterized complexity status for zonotope norm maximization and two-layer ICNN Lipschitz constants.

Aritra Das, Vincent Froese, Moritz Grillo et al. · 1 citation