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On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces

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Publication:2784803
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DOI10.1162/089976601750399263zbMath0992.68119OpenAlexW2154103954WikidataQ74409470 ScholiaQ74409470MaRDI QIDQ2784803

No author found.

Publication date: 24 April 2002

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

Full work available at URL: https://eprints.soton.ac.uk/251193/1/WaveletKernel.pdf


zbMATH Keywords

function Hilbert space


Mathematics Subject Classification ID

Computational learning theory (68Q32) Learning and adaptive systems in artificial intelligence (68T05)


Related Items

On Different Facets of Regularization Theory ⋮ Model selection approaches for non-linear system identification: a review ⋮ Sparse kernel learning with LASSO and Bayesian inference algorithm ⋮ Existence of frames based on the Szegö kernel in the Hardy space



Cites Work

  • On a kernel-based method for pattern recognition, regression, approximation, and operator inversion
  • A Cardinal Spline Approach to Wavelets
  • Continuous and Discrete Wavelet Transforms
  • Theory of Reproducing Kernels
  • A Class of Nonharmonic Fourier Series
  • A new look at the statistical model identification
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