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Identification of Nonlinear and Dependent Latent Factor Structure through Clique Search

Kim, Dale S. et al.
arXiv (All) · Papers
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machine-learningmethodology
Learning the structure of latent factor models involves two central challenges: (1) estimating the number of latent factors and (2) learning the support of the mapping from latent variables to observed variables. This is especially challenging for nonparametric regimes and nonlinear settings. We pro
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