Learning Functions of Halfspaces
Data Structures and Algorithms
2026-03-10 v1 Computational Complexity
Abstract
We give an algorithm that learns arbitrary Boolean functions of arbitrary halfspaces over , in the challenging distribution-free Probably Approximately Correct (PAC) learning model, running in time . This is the first algorithm that can PAC learn even intersections of two halfspaces in time
Cite
@article{arxiv.2603.08700,
title = {Learning Functions of Halfspaces},
author = {Josh Alman and Shyamal Patel and Rocco A. Servedio},
journal= {arXiv preprint arXiv:2603.08700},
year = {2026}
}