Georgogiannis Alexandros

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Gaussian graphical models are of great interest in statistical learning. Since the conditional independence between the variables corresponds to zero entries in the inverse covariance matrix, one can learn the structure of the graph by estimating a sparse inverse covariance matrix from sample data. This is usually done by solving a convex maximum likelihood(More)
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