Noisy Independent Factor Analysis Model for Density Estimation and Classification

  title={Noisy Independent Factor Analysis Model for Density Estimation and Classification},
  author={Umberto Amato and Anestis Antoniadis and Alexander Samarov and Alexandre B. Tsybakov},
  journal={Econometrics: Econometric \& Statistical Methods - General eJournal},
  • U. Amato, A. Antoniadis, A. Tsybakov
  • Published 9 June 2009
  • Mathematics, Computer Science
  • Econometrics: Econometric & Statistical Methods - General eJournal
We consider the problem of multivariate density estimation when the unknown density is assumed to follow a particular form of dimensionality reduction, a noisy independent factor analysis (IFA) model. In this model the data are generated by a number of latent independent components having unknown distributions and are observed in Gaussian noise. We do not assume that either the number of components or the matrix mixing the components are known. We show that the densities of this form can be… 

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