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Multiclass total variation clustering

Type of publication Peer-reviewed
Publikationsform Proceedings (peer-reviewed)
Author Bresson Xavier, Laurent Thomas, Uminsky David, Von Brecht James H.,
Project Novel Image Processing Methods for Fetal MR Imaging: 3D Reconstruction and Segmentation with Soft Priors
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Proceedings (peer-reviewed)

Title of proceedings Advances in Neural Information Processing Systems 26
Place USA

Open Access


Ideas from the image processing literature have recently motivated a new set of clustering algorithms that rely on the concept of total variation. While these algorithms perform well for bi-partitioning tasks, their recursive extensions yield unimpressive results for multiclass clustering tasks. This paper presents a general framework for multiclass total variation clustering that does not rely on recursion. The results greatly outperform previous total variation algorithms and compare well with state-of-the-art NMF approaches.