Moritz Gschwandtner

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Sparse statistical methods lead to parameter estimates that contain exact zeros. This has advantages especially in the analysis of high-dimensional data, because the contribution of single variables—potential noise variables—is set to zero. We review recent proposals for sparse methods in the context of regression and classification, and compare the(More)
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