3 papers
cs.AI2026
Quantifying Sensitivity for Tree Ensembles: A symbolic and compositional approach
Ajinkya Naik, Chaitanya Garg, S. Akshay +2
Decision tree ensembles (DTE) are a popular model for a wide range of AI classification tasks, used in multiple safety critical domains, and hence verifying properties on these mod…
cs.LO2026
Formal Reasoning About Confidence and Automated Verification of Neural Networks
Mohammad Afzal, S. Akshay, Blaise Genest +1
In the last decade, a large body of work has emerged on robustness of neural networks, i.e., checking if the decision remains unchanged when the input is slightly perturbed. Howeve…
cs.LG2026
Data-Aware and Scalable Sensitivity Analysis for Decision Tree Ensembles
Namrita Varshney, Ashutosh Gupta, Arhaan Ahmad +2
Decision tree ensembles are widely used in critical domains, making robustness and sensitivity analysis essential to their trustworthiness. We study the feature sensitivity problem…