Probability bounds for active learning in the regression problem

Ana Karina Fermin; Carenne Ludeña

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arXiv · 1212.4457

Probability bounds for active learning in the regression problem

Ana Karina Fermin·Carenne Ludeña

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Abstract

In this article we consider the problem of choosing an optimal sampling scheme for the regression problem simultaneously with that of model selection. We consider a batch type approach and an on-line approach following algorithms recently developed for the classification problem. Our main tools are concentration-type inequalities which allow us to bound the supremum of the deviations of the sampling scheme corrected by an appropriate weight function.

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Ana Karina Fermin, Carenne Ludeña. 2012-12-18. Probability bounds for active learning in the regression problem. https://arxiv.org/abs/1212.4457

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