A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions
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چکیده
In the forward phase, GreedyInverseCovariance() selects the top bs candidates by calling ForwardEvaluator() (Algorithm 1). Briefly, this algorithm checks each of the (as yet unselected) positions in the upper (or lower) triangular matrix of W and returns a map of the top bs candidates. For each candidate, αij is computed and subsequently, the likelihood when αij(eij + eji) is added to W is computed.
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تاریخ انتشار 2013