Semi-supervised active learning for support vector machines: a novel approach that exploits structure information in data

DOI10.1016/j.ins.2018.04.063zbMath1440.68202arXiv1610.03995OpenAlexW2537084562MaRDI QIDQ2198077

Adrian Calma, Bernhard Sick, Tobias Reitmaier

Publication date: 9 September 2020

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1610.03995

zbMATH Keywords

active learningsupport vector machinesemi-supervised learning4DS strategyresponsibility-weighted Mahalanobis kernelstructure information

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (4)

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Uses Software

• LIBSVM

Cites Work

• Support vector machine with manifold regularization and partially labeling privacy protection
• Sparse regularization for semi-supervised classification
• Active learning with adaptive regularization
• Two faces of active learning
• 10.1162/153244302760185243
• Training a Support Vector Machine in the Primal
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