Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform

Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning due to limited sample size. In this paper, we propose a new approach to covariance estimation, which is based on constrained maximum likelihood (ML) estimation of the covariance... (read more)

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