Robustness Verification of Tree-based Models

NeurIPS 2019 Hongge ChenHuan ZhangSi SiYang LiDuane BoningCho-Jui Hsieh

We study the robustness verification problem for tree-based models, including decision trees, random forests (RFs) and gradient boosted decision trees (GBDTs). Formal robustness verification of decision tree ensembles involves finding the exact minimal adversarial perturbation or a guaranteed lower bound of it... (read more)

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