Parametrizing Convex Sets Using Sublinear Neural Networks

arXiv:2605.03520v1 Announce Type: cross Abstract: We propose a neural parameterization of convex sets by learning sublinear (positively homogeneous and convex) functions. Our networks implicitly represent both the support and gauge functions of a convex body. We prove a universal approximation...