JMLR
Algorithms for ridge estimation with convergence guarantees
Authors
Wanli Qiao
Wolfgang Polonik
Research Topics
High-Dimensional Statistics
Computational Statistics
Paper Information
-
Journal:
Journal of Machine Learning Research -
Added to Tracker:
Dec 30, 2025
Abstract
The extraction of filamentary structure from a point cloud is discussed. The filaments are modeled as ridge lines or higher dimensional ridges of an underlying density. We propose two novel algorithms, and provide theoretical guarantees for their convergences, by which we mean that the algorithms can asymptotically recover the full ridge set. We consider the new algorithms as alternatives to the Subspace Constrained Mean Shift (SCMS) algorithm for which no such theoretical guarantees are known.
Author Details
Wanli Qiao
AuthorWolfgang Polonik
AuthorResearch Topics & Keywords
High-Dimensional Statistics
Research AreaComputational Statistics
Research AreaCitation Information
APA Format
Wanli Qiao
&
Wolfgang Polonik
.
Algorithms for ridge estimation with convergence guarantees.
Journal of Machine Learning Research
.
BibTeX Format
@article{paper703,
title = { Algorithms for ridge estimation with convergence guarantees },
author = {
Wanli Qiao
and Wolfgang Polonik
},
journal = { Journal of Machine Learning Research },
url = { https://www.jmlr.org/papers/v26/21-0095.html }
}