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We consider the group lasso penalty for the linear model. We note that the standard algorithm for solving the problem assumes that the model matrices in each group are orthonormal. Here we consider a ...
Proximal methods for the latent group lasso penalty
Structured sparsity proximal methods regularization
2012/11/23
We consider a regularized least squares problem, with regularization by structured sparsity-inducing norms, which extend the usual $\ell_1$ and the group lasso penalty, by allowing the subsets to over...
Non-asymptotic Oracle Inequalities for the Lasso and Group Lasso in high dimensional logistic model
Logistic model Lasso Group Lasso High-dimensional
2012/6/19
We consider the problem of estimating a function $f_{0}$ in logistic regression model. We propose to estimate this function $f_{0}$ by a sparse approximation build as a linear combinaison of elements ...