Corpus ID: 62828018

Graphical Lasso and Thresholding: Equivalence and Closed-form Solutions

@article{Fattahi2019GraphicalLA,
  title={Graphical Lasso and Thresholding: Equivalence and Closed-form Solutions},
  author={Salar Fattahi and Somayeh Sojoudi},
  journal={J. Mach. Learn. Res.},
  year={2019},
  volume={20},
  pages={10:1-10:44}
}
  • Salar Fattahi, Somayeh Sojoudi
  • Published 2019
  • Mathematics, Computer Science
  • J. Mach. Learn. Res.
  • Graphical Lasso (GL) is a popular method for learning the structure of an undirected graphical model, which is based on an $l_1$ regularization technique. The first goal of this work is to study the behavior of the optimal solution of GL as a function of its regularization coefficient. We show that if the number of samples is not too small compared to the number of parameters, the sparsity pattern of the optimal solution of GL changes gradually when the regularization coefficient increases from… CONTINUE READING

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