ShaplEIG: Bayesian Experimental Design for Shapley Value Estimation

ArXi:2606.02247v1 Announce Type: cross Shapley values are a principled attribution measure widely used in interpretable machine learning, but their exact computation scales exponentially with the number of players, motivating a wide range of approximation methods based on value function evaluations of sampled coalitions. This raises the question of whether approximation accuracy can be improved by adaptively selecting coalitions for evaluation based on previous evaluations.