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Clustering with tangles

By Ulrike von Luxburg, Solveig Klepper

Appears in collection : Machine Learning and Signal Processing on Graphs / Apprentissage automatique et traitement du signal sur graphes

Originally, tangles were invented as an abstract tool in mathematical graph theory to prove the famous graph minor theorem. In the talk, I will showcase the potential of tangles in machine learning applications. Given a collection of cuts of any dataset, tangles aggregate these cuts to point in the direction of a dense structure. As a result, a cluster is softly characterized by a set of consistent pointers. This highly flexible approach can solve clustering problems in various setups, ranging from questionnaires over community detection in graphs to clustering points in metric spaces.

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Citation data

  • DOI 10.24350/CIRM.V.19982203
  • Cite this video von Luxburg, Ulrike; Klepper, Solveig (10/11/2022). Clustering with tangles. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.19982203
  • URL https://dx.doi.org/10.24350/CIRM.V.19982203


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