On group-wise ℓp regularization: Theory and efficient algorithms
Following advances in compressed sensing and high-dimensional statistics, many pattern recognition methods have been developed with ℓ1 regularization, which promotes sparse solutions. In this work, we instead advocate the use of ℓp (2 ≥ p > 1) regularization in a group setting which provides a be...
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| Format: | Journal Article |
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Elsevier
2015
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| Online Access: | http://hdl.handle.net/20.500.11937/58894 |