In the framework of supervised learning we prove that the iterative algorithm introduced in Umanità and Villa (2010) allows to estimate in a consistent way the relevant features of the regression function under the a priori assumption that it admits a sparse representation.

A consistent algorithm to solve Lasso, elastic-net and Tikhonov regularization.

DE VITO, ERNESTO;VILLA, SILVIA;UMANITA', VERONICA
2011-01-01

Abstract

In the framework of supervised learning we prove that the iterative algorithm introduced in Umanità and Villa (2010) allows to estimate in a consistent way the relevant features of the regression function under the a priori assumption that it admits a sparse representation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/277329
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