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Chapitre D'ouvrage Année : 2019

Generative Histogram-Based Model Using Unsupervised Learning

Résumé

This paper presents a new generative unsupervised learning algorithm based on a representation of the clusters distribution by histograms. The main idea is to reduce the model complexity through cluster-defined projections of the data on independent axes. The results show that the proposed approach performs efficiently compared with other algorithms. In addition, it is more efficient to generate new instances with the same distribution than the training data.
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Dates et versions

hal-02994819 , version 1 (08-11-2020)

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Citer

Parisa Rastin, Guénaël Cabanes, Rosanna Verde, Younès Bennani, Thierry Couronne. Generative Histogram-Based Model Using Unsupervised Learning. Neural Information Processing, pp.634-646, 2019, ⟨10.1007/978-3-030-36718-3_53⟩. ⟨hal-02994819⟩
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