R-CTSVM+: robust capped \(\mathrm{L}_1\)-norm twin support vector machine with privileged information

DOI10.1016/J.INS.2021.06.003OpenAlexW3171582157MaRDI QIDQ6065954

Qiongjie Cui, Wenzhu Yan, Yanmeng Li, Huaijiang Sun

Publication date: 11 December 2023

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

Full work available at URL: https://doi.org/10.1016/j.ins.2021.06.003

zbMATH Keywords

classificationrobustnessprivileged informationtwin SVMcapped \(\mathrm{L}_1\)-norm

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

• A new learning paradigm: learning using privileged information
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• CTSVM: a robust twin support vector machine with correntropy-induced loss function for binary classification problems
• Robust capped L1-norm twin support vector machine
• Insensitive stochastic gradient twin support vector machines for large scale problems
• KOC+: kernel ridge regression based one-class classification using privileged information
• Robust learning with imperfect privileged information
• Global robust stability of delayed neural networks: estimating upper limit of norm of delayed connection weight matrix
• Robust L1-norm non-parallel proximal support vector machine
• Person Re-Identification With Metric Learning Using Privileged Information
• Linear Discriminant Analysis Based on L1-Norm Maximization

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Robust capped L1-norm twin support vector machine

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