Kernel Banzhaf: A Fast and Robust Estimator for Banzhaf Values

Yurong Liu, R. Teal Witter, Flip Korn, Tarfah Alrashed, Dimitris Paparas, Juliana Freire

Keywords: Banzhaf values, Shapley values, Kernel SHAP, Leverage Scores, Least Squares Regression

Abstract: Banzhaf values offer a simple and interpretable alternative to the widely-used Shapley values. We introduce Kernel Banzhaf, a novel algorithm inspired by KernelSHAP, that leverages an elegant connection between Banzhaf values and linear regression. Through extensive experiments on feature attribution tasks, we demonstrate that Kernel Banzhaf substantially outperforms other algorithms for estimating Banzhaf values in both sample efficiency and robustness to noise. Furthermore, we prove theoretical guarantees on the algorithm's performance, establishing Kernel Banzhaf as a valuable tool for interpretable machine learning.

Primary Area: interpretability and explainable AI

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Submission Number: 4866