Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical Lasso
Résumé
We provide a framework and algorithm for tuning the hyperparameters of the Graphical Lasso via a bilevel optimization
problem solved with a first-order method. In particular, we derive the Jacobian of the Graphical Lasso solution with respect to its
regularization hyperparameters.
| Origine | Fichiers produits par l'(les) auteur(s) |
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