The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction 事件

The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction arXiv:2605.29411v1 Announce Type: cross Abstract: Under standard graphical assumptions, the Markov boundary of a target variable is the smallest set of features that renders every other feature redundant. Once the boundary is observed, the target is conditionally independent of the rest of the table. This is a tempting object for tabular prediction, since it names exactly the columns a model should need. Yet modern regres