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CORR
2007
Springer
164views Education» more  CORR 2007»
13 years 5 months ago
Consistency of the group Lasso and multiple kernel learning
We consider the least-square regression problem with regularization by a block 1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, r...
Francis Bach
CORR
2010
Springer
171views Education» more  CORR 2010»
13 years 3 months ago
Graphical Models Concepts in Compressed Sensing
This paper surveys recent work in applying ideas from graphical models and message passing algorithms to solve large scale regularized regression problems. In particular, the focu...
Andrea Montanari
CSDA
2007
120views more  CSDA 2007»
13 years 5 months ago
Boosting ridge regression
Ridge regression is a well established method to shrink regression parameters towards zero, thereby securing existence of estimates. The present paper investigates several approac...
Gerhard Tutz, Harald Binder
ICML
2009
IEEE
14 years 6 months ago
Blockwise coordinate descent procedures for the multi-task lasso, with applications to neural semantic basis discovery
We develop a cyclical blockwise coordinate descent algorithm for the multi-task Lasso that efficiently solves problems with thousands of features and tasks. The main result shows ...
Han Liu, Mark Palatucci, Jian Zhang
JMLR
2010
110views more  JMLR 2010»
13 years 3 days ago
Exploiting Covariate Similarity in Sparse Regression via the Pairwise Elastic Net
A new approach to regression regularization called the Pairwise Elastic Net is proposed. Like the Elastic Net, it simultaneously performs automatic variable selection and continuo...
Alexander Lorbert, David Eis, Victoria Kostina, Da...