adaptive binning

Adaptive Binning Boosts Self-Supervised Learning on Medical Tabular Data, Researchers Report

Researchers propose Adaptive Binning, a training-adaptive discretization pretext for tabular self-supervised learning. The method progressively refines discretization per feature and uses a heterogeneity-aware objective. Experiments on public medical tabular datasets show consistent gains over fixed binning approaches.