Nonparametric Sparsity and Regularization

In this work we are interested in the problems of supervised learning and variable selection when the input-output dependence is described by a nonlinear function depending on a few variables. Our goal is to consider a sparse nonparametric model, hence avoiding linear or additive models. The key ide...

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Bibliographic Details
Main Authors: Rosasco, Lorenzo Andrea, Villa, Silvia, Mosci, Sofia, Santoro, Matteo, Verri, Alessandro
Other Authors: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Format: Article
Language:en_US
Published: Association for Computing Machinery (ACM) 2013
Online Access:http://hdl.handle.net/1721.1/81424
https://orcid.org/0000-0001-6376-4786