Oracle inequalities for convex loss functions with nonlinear targets
This article considers penalized empirical loss minimization of convex loss functions with unknown target functions. Using the elastic net penalty, of which the Least Absolute Shrinkage and Selection Operator (Lasso) is a special case, we establish a finite sample oracle inequality which bounds the...
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| Formato: | Journal article |
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Taylor and Francis
2015
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