Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence

arXiv:2402.12930v1 Announce Type: new
Abstract: Finding and describing sub-populations that are exceptional regarding a target property has important applications in many scientific disciplines, from identifying disadvantaged demographic groups in census data to finding conductive molecules within gold nanoparticles. Current approaches to finding such subgroups require pre-discretized predictive variables, do not permit non-trivial target distributions, do not scale to large datasets, and struggle to find diverse results.
To address these limitations, we propose Syflow, an end-to-end optimizable approach in which we …

abstract applications arxiv census cs.lg current data divergence kl-divergence molecules predictive property subgroups type variables