Evgenii Kuriabov

Optimized Instance Alteration for Explaining and Assessing Robustness of Classifiers

This work proposes a unified approach for diagnosing misclassification and assessing the robustness of black-box classifiers using an optimization framework that modifies an instance so that the classifier predicts a specified target label, while ensuring that the modification remains easily explainable.