Abstract:
In the framework of supervised learning we prove that the iterative algorithm introduced in previous paper 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 on a fixed dictionary.
Keywords:
Learning theory, Regularization, Sparsity, Consistent estimator
MSC:
60, 49
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