Knowledge transfer in SVM and neural networks

DOI10.1007/s10472-017-9538-xzbMath1422.68207OpenAlexW2590235073MaRDI QIDQ1680840

Vladimir Vapnik, Rauf Izmailov

Publication date: 16 November 2017

Published in: Annals of Mathematics and Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10472-017-9538-x

zbMATH Keywords

classificationneural networklearning theoryknowledge representationframesregressionsupport vector machineprivileged informationknowledge transferintelligent teachersimilarity control

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Knowledge representation (68T30)

Related Items (5)

Adaptive kernel scaling support vector machine with application to a prostate cancer image study ⋮ Blessing of dimensionality at the edge and geometry of few-shot learning ⋮ Optimal control using to approximate probability distribution of observation set ⋮ Rethinking statistical learning theory: learning using statistical invariants ⋮ Efficient implicit Lagrangian twin parametric insensitive support vector regression via unconstrained minimization problems

Uses Software

• Matlab
• UCI-ml
• Neural Network Toolbox

Cites Work

• A new learning paradigm: learning using privileged information
• Estimation of Dependences Based on Empirical Data
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