Theory for ℓ1/ℓ2-penalty procedures

  • Peter BühlmannEmail author
  • Sara van de Geer
Part of the Springer Series in Statistics book series (SSS)


We study four procedures for regression models with group structure in the parameter vector. The first two are for models with univariate response variable. They are the so-called group Lasso (see Chapter 4), and the smoothed group Lasso for the high-dimensional additive model (see Chapter 5). We also discuss multivariate extensions, namely for the linear model with time-varying coefficients, for multivariate regression, and multitask learning.


Regularization Parameter Empirical Process Error Loss Truncation Level Group Lasso 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Seminar for StatisticsETH ZürichZürichSwitzerland

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