Learning convex polyhedra with margin
Machine Learning
2021-11-03 v3 Computational Complexity
Computational Geometry
Machine Learning
Abstract
We present an improved algorithm for {\em quasi-properly} learning convex polyhedra in the realizable PAC setting from data with a margin. Our learning algorithm constructs a consistent polyhedron as an intersection of about halfspaces with constant-size margins in time polynomial in (where is the number of halfspaces forming an optimal polyhedron). We also identify distinct generalizations of the notion of margin from hyperplanes to polyhedra and investigate how they relate geometrically; this result may have ramifications beyond the learning setting.
Cite
@article{arxiv.1805.09719,
title = {Learning convex polyhedra with margin},
author = {Lee-Ad Gottlieb and Eran Kaufman and Aryeh Kontorovich and Gabriel Nivasch},
journal= {arXiv preprint arXiv:1805.09719},
year = {2021}
}