著者: Yang Zhou , Rong Jin , Steven C. H. Hoi - International Conference on Artificial Intelligence and Statistics, AISTATS 2010 被引用: 176
We propose a novel group regularization which we call exclusive lasso. Unlike the group lasso regularizer that assumes covarying variables in groups, the proposed exclusive lasso regularizer models the scenario when variables in the same group compete with each other. Analysis is presented to illustrate the properties of the proposed regularizer. We present a framework of kernel based multi-task feature selection algorithm basedontheproposedexclusivelassoregularizer. An efficient algorithmis derivedtosolve the related optimization problem. Experiments with document categorization show that our approach outperforms state-of-theart algorithms for multi-task feature selection. 1
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