no code implementations • 21 Oct 2020 • Dhananjay Ashok, Joseph Scott, Sebastian Wetzel, Maysum Panju, Vijay Ganesh
Our method, logic-guided genetic algorithm (LGGA), takes as input a set of labelled data points and auxiliary truths (ATs) (mathematical facts known a priori about the unknown function the regressor aims to learn) and outputs a specially generated and curated dataset that can be used with any SR method.