DROPS

Document

DOI: 10.4230/LIPIcs.WADS.2025.3

Support Vector Machines in the Hilbert Geometry

Authors: Aditya Acharya, Auguste H. Gezalyan, Julian Vanecek, David M. Mount, and Sunil Arya

Published in: LIPIcs, Volume 349, 19th International Symposium on Algorithms and Data Structures (WADS 2025)

Abstract

Support Vector Machines (SVMs) are a class of classification models in machine learning that are based on computing a maximum-margin separator between two sets of points. The SVM problem has been heavily studied for Euclidean geometry and for a number of kernels. In this paper, we consider the linear SVM problem in the Hilbert metric, a non-Euclidean geometry defined over a convex body. We present efficient algorithms for computing the SVM classifier for a set of n points in the Hilbert metric defined by convex polygons in the plane and convex polytopes in d-dimensional space. We also consider the problems in the related Funk distance.

Cite as

Aditya Acharya, Auguste H. Gezalyan, Julian Vanecek, David M. Mount, and Sunil Arya. Support Vector Machines in the Hilbert Geometry. In 19th International Symposium on Algorithms and Data Structures (WADS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 349, pp. 3:1-3:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

Copy BibTex To Clipboard

@InProceedings{acharya_et_al:LIPIcs.WADS.2025.3,
  author =	{Acharya, Aditya and Gezalyan, Auguste H. and Vanecek, Julian and Mount, David M. and Arya, Sunil},
  title =	{{Support Vector Machines in the Hilbert Geometry}},
  booktitle =	{19th International Symposium on Algorithms and Data Structures (WADS 2025)},
  pages =	{3:1--3:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-398-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{349},
  editor =	{Morin, Pat and Oh, Eunjin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WADS.2025.3},
  URN =		{urn:nbn:de:0030-drops-242348},
  doi =		{10.4230/LIPIcs.WADS.2025.3},
  annote =	{Keywords: Support vector machines, Hilbert geometry, linear classification, machine learning, LP-type problems}
}

Search Results

Documents authored by Vanecek, Julian

Support Vector Machines in the Hilbert Geometry

Abstract

Cite as

Thanks for your feedback!

Could not send message