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Probability bounds for active learning i...

Fermin, Ana Karina...

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Probability bounds for active learning in the regression problem by Fermin, Ana Karina ( Author )

Content Provider	Lemonjar Open Access
Publisher	N.A
Publication Date	26-07-2023
Summary	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.
ISBN	-
Item Type	Article
File Type	pdf
File Size	37.08 KB
Language	English
Subjects	-
Unlimited	MYR 0.01
Total read	-
URL	http://arxiv.org/abs/1212.4457

Citation

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AMA 11th EditionReferences

Fermin, Ana Karina. Probability bounds for active learning in the regression problem. N.A. July 26, 2023. Accessed September 20, 2024. https://online.provdatabase.com/cite/5838

APA 7th EditionReferences

Fermin, Ana Karina. (2023). Probability bounds for active learning in the regression problem. N.A. https://online.provdatabase.com/cite/5838

Chicago 17th EditionReferences

Fermin, Ana Karina. Probability bounds for active learning in the regression problem. N.A. 2023. https://online.provdatabase.com/cite/5838

HarvardReferences

Fermin, Ana Karina. (2023). Probability bounds for active learning in the regression problem. [Online]. N.A. Available from: https://online.provdatabase.com/cite/5838. (Accessed 20 September 2024).

Harvard AustraliaReferences

Fermin, Ana Karina, 2023, Probability bounds for active learning in the regression problem, N.A, viewed 20 September 2024, <https://online.provdatabase.com/cite/5838>

MLA 9th EditionWorks Cited

Fermin, Ana Karina. Probability bounds for active learning in the regression problem. N.A, 2023. PROV Database, https://online.provdatabase.com/cite/5838.

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