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Title:

Exact block-wise optimization in group lasso and sparse group lasso for linear regression

Document type:
Zeitschriftenaufsatz
Author(s):
Foygel, Rina; Drton, Mathias
Abstract:
The group lasso is a penalized regression method, used in regression problems where the covariates are partitioned into groups to promote sparsity at the group level. Existing methods for finding the group lasso estimator either use gradient projection methods to update the entire coefficient vector simultaneously at each step, or update one group of coefficients at a time using an inexact line search to approximate the optimal value for the group of coefficients when all other groups' coefficie...     »
Dewey Decimal Classification:
510 Mathematik
Journal title:
Preprint
Year:
2010
Language:
en
WWW:
Arxiv
Submitted:
16.10.2010
Format:
Text
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