A batch ensemble approach to active learning with model selection

DOI10.1016/j.neunet.2008.06.004zbMath1254.68226OpenAlexW2104665533WikidataQ44942132 ScholiaQ44942132MaRDI QIDQ1932092

Neil Rubens, Masashi Sugiyama

Publication date: 17 January 2013

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2008.06.004

zbMATH Keywords

model selectionimportance samplinglinear regressionactive learninggeneralization errorsequential learningcovariate shiftbatch learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Improving importance estimation in pool-based batch active learning for approximate linear regression, Pool-based active learning in approximate linear regression, Learning what we don't care about: anti-training with sacrificial functions, Active Data Collection for Efficient Estimation and Comparison of Nonlinear Neural Models

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