mlsanityData to 7 Oct 2026

Moving Up the Cluster Tree with the Gradient Flow

arXiv 2109.08362 ↗First posted 17 Sep 2021math.ST stat.ML stat.THcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 8 of its 73 references that are in the map. First posted on arXiv 17 Sep 2021.

Builds on

8 of 73 references.

References · 8

  1. 2014A Population Background for Nonparametric Density-Based Clusteringcited by 14
  2. 2015Density Level Sets: Asymptotics, Inference, and Visualizationcited by 11
  3. 2014Consistent procedures for cluster tree estimation and pruningcited by 9
  4. 2018The modal age of Statisticscited by 9
  5. 2013Nonparametric Inference For Density Modescited by 5
  6. 2015Beyond Hartigan Consistency: Merge Distortion Metric for Hierarchical Clusteringcited by 5
  7. 2014Fully adaptive density-based clusteringcited by 4
  8. 2015Statistical Inference using the Morse-Smale Complexcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 0; 2026: 1.

3 papers.