Localized Randomized Smoothing for Collective Robustness Certification

arXiv:2210.16140v3 Announce Type: replace
Abstract: Models for image segmentation, node classification and many other tasks map a single input to multiple labels. By perturbing this single shared input (e.g. the image) an adversary can manipulate several predictions (e.g. misclassify several pixels). Collective robustness certification is the task of provably bounding the number of robust predictions under this threat model. The only dedicated method that goes beyond certifying each output independently is limited to strictly local models, where each prediction is …

abstract arxiv certification classification collective cs.cv cs.lg image labels map multiple node pixels predictions robustness segmentation tasks type