Before revision:  As a result, we can use a recent randomized algorithm to solve the problem, which offers an approximation factor of 1/e . Finally, we illustrate our theoretical findings by performing experiments on synthetic and real lending data .
After revision:  As a result, we can use a recent randomized algorithm to solve the problem, which offers an approximation factor of 1/e . Finally, we demonstrate that, by incorporating a matroid constraint into the problem formulation, we can increase the diversity of the optimal set of counterfactual explanations and incentivize individuals across the whole spectrum of the population to self improve. Experiments on synthetic and real lending data .