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Communication Dans Un Congrès Année : 2011

Clusterpath An Algorithm for Clustering using Convex Fusion Penalties

Résumé

We present a new clustering algorithm by proposing a convex relaxation of hierarchical clustering, which results in a family of objective functions with a natural geometric interpretation. We give efficient algorithms for calculating the continuous regularization path of solutions, and discuss relative advantages of the parameters. Our method experimentally gives state-of-the-art results similar to spectral clustering for non-convex clusters, and has the added benefit of learning a tree structure from the data.
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Dates et versions

hal-00591630 , version 1 (09-05-2011)

Identifiants

  • HAL Id : hal-00591630 , version 1

Citer

Toby Dylan Hocking, Armand Joulin, Francis Bach, Jean-Philippe Vert. Clusterpath An Algorithm for Clustering using Convex Fusion Penalties. 28th international conference on machine learning, Jun 2011, United States. pp.1. ⟨hal-00591630⟩
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