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A Pathwise Algorithm for Covariance Selection

A Pathwise Algorithm for Covariance Selection

This video was recorded at NIPS Workshops, Whistler 2009. Covariance selection seeks to estimate a covariance matrix by maximum likelihood while restricting the number of nonzero inverse covariance matrix coefficients. A single penalty parameter usually controls the tradeoff between log likelihood and sparsity in the inverse matrix. We describe an efficient algorithm for computing a full regularization path of solutions to this problem.... Show More

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