Robust capped L1-norm twin support vector machine

DOI10.1016/j.neunet.2019.01.016zbMath1434.68465OpenAlexW2916315887WikidataQ92414170 ScholiaQ92414170MaRDI QIDQ2183604

Peng Luo, Liyong Fu, Ning Ye, Qiaolin Ye, ChunYan Wang

Publication date: 27 May 2020

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

Full work available at URL: https://doi.org/10.1016/j.neunet.2019.01.016

zbMATH Keywords

robustnessmachine learningcapped L1-normTWSVM

Mathematics Subject Classification ID

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

Related Items (7)

Twin support vector machines with privileged information ⋮ R-CTSVM+: robust capped \(\mathrm{L}_1\)-norm twin support vector machine with privileged information ⋮ Capped \(L_{2,p}\)-norm metric based robust least squares twin support vector machine for pattern classification ⋮ Adaptive robust adaboost-based twin support vector machine with universum data ⋮ Robust capped L1-norm projection twin support vector machine ⋮ Stochastic nonlocal damage analysis by a machine learning approach ⋮ Correntropy-based metric for robust twin support vector machine

Cites Work

• Improve robustness of sparse PCA by \(L_{1}\)-norm maximization
• MLTSVM: a novel twin support vector machine to multi-label learning
• Support-vector networks
• Robust L1-norm non-parallel proximal support vector machine
• A feature selection method for nonparallel plane support vector machine classification
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