Complexity-Budgeted, Interaction-Aware Interpretable Model for Tabular Data
DGX agentarXiv:2607.07060v1 Announce Type: cross Abstract: Inherently interpretable classifiers for tabular data typically rely on sparse features, rules, or patterns that users can inspect directly. The margi