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Pré-Publication, Document De Travail Année : 2010

A Stochastic Algorithm for Probabilistic Independent Component Analysis

Résumé

The decomposition of a sample of images on a relevant subspace is a recurrent problem in many different fields from Computer Vision to medical image analysis. We propose in this paper a new learning principle and implementation of the generative decomposition model generally known as noisy ICA (for independent component analysis) based on the SAEM algorithm, which is a versatile stochastic approximation of the standard EM algorithm. We demonstrate the applicability of the method on a large range of decomposition models and illustrate the developments with experimental results on various data sets.
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Dates et versions

hal-00511165 , version 1 (24-08-2010)

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  • HAL Id : hal-00511165 , version 1

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Stéphanie Allassonniere, Laurent Younes. A Stochastic Algorithm for Probabilistic Independent Component Analysis. 2010. ⟨hal-00511165⟩
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