Knowledge-driven Active Learning
Knowledge-driven Active Learning
About this item
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Publisher
Ithaca: Cornell University Library, arXiv.org
Journal title
Language
English
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Publication information
Publisher
Ithaca: Cornell University Library, arXiv.org
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Scope and Contents
Contents
The deployment of Deep Learning (DL) models is still precluded in those contexts where the amount of supervised data is limited. To answer this issue, active learning strategies aim at minimizing the amount of labelled data required to train a DL model. Most active strategies are based on uncertain sample selection, and even often restricted to sam...
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Full title
Knowledge-driven Active Learning
Authors, Artists and Contributors
Author / Creator
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TN_cdi_proquest_journals_2583229245
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2583229245
Other Identifiers
E-ISSN
2331-8422
DOI
10.48550/arxiv.2110.08265
