Moving Up the Cluster Tree with the Gradient Flow
Statistics Theory
2021-12-13 v2 Machine Learning
Statistics Theory
Abstract
The paper establishes a strong correspondence between two important clustering approaches that emerged in the 1970's: clustering by level sets or cluster tree as proposed by Hartigan and clustering by gradient lines or gradient flow as proposed by Fukunaga and Hostetler. We do so by showing that we can move up the cluster tree by following the gradient ascent flow.
Cite
@article{arxiv.2109.08362,
title = {Moving Up the Cluster Tree with the Gradient Flow},
author = {Ery Arias-Castro and Wanli Qiao},
journal= {arXiv preprint arXiv:2109.08362},
year = {2021}
}
Comments
This is an expanded version. We changed the title to better reflect the contribution made in the paper