https://github.com/computorg/published-202412-ambroise-spectral

Spectral Bridges: Scalable Spectral Clustering Based on Vector Quantization
https://github.com/computorg/published-202412-ambroise-spectral

non-parametric scalable spectral-clustering vector-quantization

Last synced: about 10 hours ago
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Spectral Bridges: Scalable Spectral Clustering Based on Vector Quantization

• Host: GitHub
• URL: https://github.com/computorg/published-202412-ambroise-spectral
• Owner: computorg
• License: cc-by-4.0
• Created: 2024-12-13T10:05:28.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-09-12T14:20:32.000Z (10 months ago)
• Last Synced: 2026-02-09T05:32:37.630Z (5 months ago)
• Topics: non-parametric, scalable, spectral-clustering, vector-quantization
• Language: Python
• Homepage: http://computo-journal.org/published-202412-ambroise-spectral/
• Size: 10.2 MB
• Stars: 0
• Watchers: 3
• Forks: 3
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Spectral Bridges

Félix Laplante, Christophe Ambroise

2024-12-13

### Citation

Félix Laplante and Christophe Ambroise (December 2024). Spectral Bridges. Computo.

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### Authors’ affiliations

- Félix Laplante (Université Paris-Saclay, CNRS, Univ Evry,)

- [Christophe Ambroise](https://cambroise.github.io/) (Université Paris-Saclay, CNRS, Univ Evry,)

### Abstract

In this paper, Spectral Bridges, a novel clustering algorithm, is

introduced. This algorithm builds upon the traditional k-means and

spectral clustering frameworks by subdividing data into small Voronoï

regions, which are subsequently merged according to a connectivity

measure. Drawing inspiration from Support Vector Machine’s margin

concept, a non-parametric clustering approach is proposed, building an

affinity margin between each pair of Voronoï regions. This approach

delineates intricate, non-convex cluster structures and is robust to

hyperparameter choice. The numerical experiments underscore Spectral

Bridges as a fast, robust, and versatile tool for clustering tasks

spanning diverse domains. Its efficacy extends to large-scale scenarios

encompassing both real-world and synthetic datasets. The Spectral Bridge

algorithm is implemented both in Python

() and R

).