Safety3h ago
New Framework Certifies MLP Adversarial Robustness
A new theoretical framework reduces adversarial robustness in Multilayered Perceptrons to a lattice traversal problem. The method identifies axis-aligned hyper-rectangles where model predictions remain constant despite input perturbations. This provides a rigorous way to certify sound and complete intervals. Practitioners can now more precisely define the boundaries where a classifier's output is guaranteed to hold.