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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...
Group descent algorithms for nonconvex penalized linear and logistic regression models with grouped predictors
Group descent algorithms nonconvex penalized linear model logistic regression model grouped predictors
2012/11/22
Penalized regression is an attractive framework for variable selection problems. Often, variables possess a grouping structure, and the relevant selection problem is that of selecting groups, not indi...
Improved Partial Least Square and Multi-group Structural Equation Model Using Distributed Computing
Structural Equation Model Partial least square Iterative initial value Multi-group Distributed Computing
2011/11/12
Structural equation model has become a very popular data-analytic technique. It is widely applied in Psychology and Sociology as well as other fields, especially in Customer Satisfaction Index (CSI) m...
We study the model theory of covers of groups definable in o-minimal structures. This includes the case of covers of compact real Lie groups. In particular we study categoricity questions, pointing ou...