The Latent Bernoulli-Gauss Model for Data Analysis

Computer Science – Learning

Scientific paper

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Scientific paper

We present a new latent-variable model employing a Gaussian mixture
integrated with a feature selection procedure (the Bernoulli part of the model)
which together form a "Latent Bernoulli-Gauss" distribution. The model is
applied to MAP estimation, clustering, feature selection and collaborative
filtering and fares favorably with the state-of-the-art latent-variable models.

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