Scalable Gaussian kernel support vector machines with sublinear training time complexity

DOI10.1016/J.INS.2017.08.033zbMath1436.68299OpenAlexW2743943492MaRDI QIDQ780936

Shizhong Liao, Chang Feng

Publication date: 16 July 2020

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

Full work available at URL: https://doi.org/10.1016/j.ins.2017.08.033

zbMATH Keywords

scalabilityGaussian kernelsubsamplingsupport vector machines (SVMs)parallel linear SVMsrandom Fourier feature mapping

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

A high-order norm-product regularized multiple kernel learning framework for kernel optimization ⋮ Direct symbol decoding using GA-SVM in chaotic baseband wireless communication system

Uses Software

• CONV_QP
• LIBSVM
• LIBLINEAR

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