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Kernelization of matrix updates, when and how?

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Publication:465262
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DOI10.1016/j.tcs.2014.09.031zbMath1360.68719OpenAlexW2174677872MaRDI QIDQ465262

Manfred K. Warmuth, Shui-sheng Zhou, Wojciech Kotłowski

Publication date: 31 October 2014

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2014.09.031


zbMATH Keywords

rotational invariancekernelizationmultiplicative updatesexponentiated gradient algorithmgradient descent algorithm


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Matrix exponential and similar functions of matrices (15A16)




Cites Work

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  • Some results on Tchebycheffian spline functions and stochastic processes
  • 10.1162/153244301753683726
  • Kernelization of Matrix Updates, When and How?
  • Prototype Classification: Insights from Machine Learning
  • A theory of the learnable
  • Competitive On-line Statistics
  • Online Variance Minimization
  • Learning Theory
  • Relative loss bounds for on-line density estimation with the exponential family of distributions


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