Coupling privileged kernel method for multi-view learning

DOI10.1016/j.ins.2018.12.058zbMath1443.68157OpenAlexW2907934539WikidataQ128672063 ScholiaQ128672063MaRDI QIDQ2005508

Jingjing Tang, Gang Kou, Dalian Liu, Ying-Jie Tian

Publication date: 8 October 2020

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

Full work available at URL: https://doi.org/10.1016/j.ins.2018.12.058

zbMATH Keywords

support vector machineprivileged informationmulti-view learningcomplementarity principlecoupling termconsensus principle

Mathematics Subject Classification ID

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

Related Items (8)

Coupling loss and self-used privileged information guided multi-view transfer learning ⋮ R-CTSVM+: robust capped \(\mathrm{L}_1\)-norm twin support vector machine with privileged information ⋮ Robust cost-sensitive kernel method with Blinex loss and its applications in credit risk evaluation ⋮ Incomplete-view oriented kernel learning method with generalization error bound ⋮ A high-order norm-product regularized multiple kernel learning framework for kernel optimization ⋮ KOC+: kernel ridge regression based one-class classification using privileged information ⋮ Simultaneous learning coefficient matrix and affinity graph for multiple kernel clustering ⋮ Multi-view Gaussian processes with posterior consistency

Uses Software

• SHOGUN
• SimpleMKL

Cites Work

• Convergence analysis of kernel canonical correlation analysis: theory and practice
• Joint multi-view representation and image annotation via optimal predictive subspace learning
• Consensus and complementarity based maximum entropy discrimination for multi-view classification
• 10.1162/153244303321897690
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