English

Fitting a Simplicial Complex using a Variation of k-means

Machine Learning 2016-08-03 v2 Computational Geometry Machine Learning

Abstract

We give a simple and effective two stage algorithm for approximating a point cloud SRm\mathcal{S}\subset\mathbb{R}^m by a simplicial complex KK. The first stage is an iterative fitting procedure that generalizes k-means clustering, while the second stage involves deleting redundant simplices. A form of dimension reduction of S\mathcal{S} is obtained as a consequence.

Keywords

Cite

@article{arxiv.1607.03849,
  title  = {Fitting a Simplicial Complex using a Variation of k-means},
  author = {Piotr Beben},
  journal= {arXiv preprint arXiv:1607.03849},
  year   = {2016}
}
R2 v1 2026-06-22T14:53:49.796Z