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Sparse Inverse Covariance Estimation via an Adaptive Gradient-Based Method
Sparse Covariance Estimation Adaptive Gradient-Based Method
2011/7/6
We study the problem of estimating from data, a sparse approximation to the inverse covariance matrix. Estimating a sparsity constrained inverse covariance matrix is a key component in Gaussian graphi...
Sparse Inverse Covariance Estimation via the Split Bregman Method
Machine Learning (stat.ML) Learning (cs.LG)
2010/12/17
We consider the problem of learning the structure of graphical models by estimating the inverse covariance matrix with sparsity regularization. We develop a new method based on split Bregman to solve ...
Missing values and sparse inverse covariance estimation
Missing values sparse inverse covariance estimation
2010/3/19
We propose an `1-regularized likelihood method for estimating the inverse
covariance matrix in the high-dimensional multivariate normal model
in presence of missing data. Our method is based on the ...