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The effectiveness of using raking duals as reusable scores for improving rare-class ranking for improving rare-class ranking while retaining classifiers trained at the original class prior is demonstrated.
Broken adaptive ridge (BAR) penalty approximates $L_0$-regularization through iterative reweighting of L2 penalties. This penalty enjoys both the oracle property and the grouping effect for highly correlated covariates, making it particularly attractive for penalized regression with complex dependence among predictors....
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