Although all flavors of sCI follow this rough algorithm, they differ on the specifics of how to achieve the goal: for example, there are deterministic, 2,4,7-20 stochastic, and semistochastic variations of sCI methods. The crucial ingredient is the searching/ranking of determinants and the pruning of determinants no longer deemed significant. Although several heuristics have been developed to achieve these goals, one open question is whether or not these heuristics can be learned and improved upon via a machine learning (ML) approach.