Sparse Cholesky covariance parametrization for recovering latent structure in ordered data

2 Jun 2020Irene CórdobaConcha BielzaPedro LarrañagaGherardo Varando

The sparse Cholesky parametrization of the inverse covariance matrix can be interpreted as a Gaussian Bayesian network; however its counterpart, the covariance Cholesky factor, has received, with few notable exceptions, little attention so far, despite having a natural interpretation as a hidden variable model for ordered signal data. To fill this gap, in this paper we focus on arbitrary zero patterns in the Cholesky factor of a covariance matrix... (read more)

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