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Consistency of the Group Lasso and Multiple Kernel Learning

Journal of Machine Learning Research, (2008): 1179-1225

Cited: 782|Views23
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Abstract

We consider the least-square regression problem with regularization by a block l1-norm, that is, a sum of Euclidean norms over spaces of dimensions larger than one. This problem, referred to as the group Lasso, extends the usual regularization by the l1-norm where all spaces have dimension one, where it is commonly referred to as the Lass...More

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