On the prediction loss of the lasso in the partially labeled setting

20 Jun 2016Pierre C. BellecArnak S. DalalyanEdwin GrappinQuentin Paris

In this paper we revisit the risk bounds of the lasso estimator in the context of transductive and semi-supervised learning. In other terms, the setting under consideration is that of regression with random design under partial labeling... (read more)

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