ONLINE REGRESSION WITH VARYING GAUSSIANS AND NON-IDENTICAL DISTRIBUTIONS

DOI10.1142/S0219530511001923zbMath1253.68189OpenAlexW2040468026MaRDI QIDQ3096972

Ting Hu

Publication date: 15 November 2011

Published in: Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0219530511001923

zbMATH Keywords

online learningreproducing kernel Hilbert spaceGaussian kernelconvex loss functionregression algorithmvariance of Gaussian

Mathematics Subject Classification ID

Computational learning theory (68Q32) Learning and adaptive systems in artificial intelligence (68T05) Online algorithms; streaming algorithms (68W27)

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Cites Work

• Derivative reproducing properties for kernel methods in learning theory
• Fully online classification by regularization
• Online learning algorithms
• On the Generalization Ability of On-Line Learning Algorithms
• An Explicit Description of the Reproducing Kernel Hilbert Spaces of Gaussian RBF Kernels
• Online Regularized Classification Algorithms
• ONLINE LEARNING WITH MARKOV SAMPLING
• ESTIMATING THE APPROXIMATION ERROR IN LEARNING THEORY
• Online Classification with Varying Gaussians

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