Information theoretic clustering using minimal spanning trees

A. Müller, S. Nowozin, C. Lampert, in:, Springer, 2012, pp. 205–215.

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Conference Paper | Published | English
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Department
Series Title
LNCS
Abstract
In this work we propose a new information-theoretic clustering algorithm that infers cluster memberships by direct optimization of a non-parametric mutual information estimate between data distribution and cluster assignment. Although the optimization objective has a solid theoretical foundation it is hard to optimize. We propose an approximate optimization formulation that leads to an efficient algorithm with low runtime complexity. The algorithm has a single free parameter, the number of clusters to find. We demonstrate superior performance on several synthetic and real datasets.
Publishing Year
Date Published
2012-08-14
Volume
7476
Page
205 - 215
Conference
DAGM: German Association For Pattern Recognition
Conference Location
Graz, Austria
Conference Date
2012-08-28 – 2012-08-31
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Müller A, Nowozin S, Lampert C. Information theoretic clustering using minimal spanning trees. In: Vol 7476. Springer; 2012:205-215. doi:10.1007/978-3-642-32717-9_21
Müller, A., Nowozin, S., & Lampert, C. (2012). Information theoretic clustering using minimal spanning trees (Vol. 7476, pp. 205–215). Presented at the DAGM: German Association For Pattern Recognition, Graz, Austria: Springer. https://doi.org/10.1007/978-3-642-32717-9_21
Müller, Andreas, Sebastian Nowozin, and Christoph Lampert. “Information Theoretic Clustering Using Minimal Spanning Trees,” 7476:205–15. Springer, 2012. https://doi.org/10.1007/978-3-642-32717-9_21.
A. Müller, S. Nowozin, and C. Lampert, “Information theoretic clustering using minimal spanning trees,” presented at the DAGM: German Association For Pattern Recognition, Graz, Austria, 2012, vol. 7476, pp. 205–215.
Müller A, Nowozin S, Lampert C. 2012. Information theoretic clustering using minimal spanning trees. DAGM: German Association For Pattern Recognition, LNCS, vol. 7476. 205–215.
Müller, Andreas, et al. Information Theoretic Clustering Using Minimal Spanning Trees. Vol. 7476, Springer, 2012, pp. 205–15, doi:10.1007/978-3-642-32717-9_21.

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