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Conference Papers Year : 2012

Generative topographic mapping and factor analyzers

Rodolphe Priam
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Mohamed Nadif
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Abstract

By embedding random factors in the Gaussian mixture model (GMM), we propose a new model called faGTM. Our approach is based on a flexible hierarchical prior for a generalization of the generative topographic mapping (GTM) and the mixture of principal components analyzers (MPPCA). The parameters are estimated with expectation-maximization and maximum a posteriori. Empirical experiments show the interest of our proposal.
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Dates and versions

hal-01916220 , version 1 (08-11-2018)

Identifiers

  • HAL Id : hal-01916220 , version 1

Cite

Rodolphe Priam, Mohamed Nadif. Generative topographic mapping and factor analyzers. Proceeding of the 1st International Conference on Pattern Recognition Applications and Methods, Feb 2012, Vilamoura, Portugal. pp.284-287. ⟨hal-01916220⟩
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