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ERM scheme for quantile regression

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Publication:369725
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DOI10.1155/2013/148490zbMath1272.68346OpenAlexW1977311439WikidataQ58915365 ScholiaQ58915365MaRDI QIDQ369725

Dao-Hong Xiang

Publication date: 19 September 2013

Published in: Abstract and Applied Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2013/148490


zbMATH Keywords

error analysisquantile regressionERM scheme


Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Learning and adaptive systems in artificial intelligence (68T05)


Related Items (1)

Learning rates for the kernel regularized regression with a differentiable strongly convex loss



Cites Work

  • Unnamed Item
  • Unnamed Item
  • Approximation analysis of learning algorithms for support vector regression and quantile regression
  • Learning gradients on manifolds
  • Classification with non-i.i.d. sampling
  • Learning with varying insensitive loss
  • The covering number in learning theory
  • Conditional quantiles with varying Gaussians
  • Convergence analysis of online algorithms
  • Learning Theory
  • ONLINE LEARNING WITH MARKOV SAMPLING
  • ESTIMATING THE APPROXIMATION ERROR IN LEARNING THEORY
  • On Complexity Issues of Online Learning Algorithms
  • Theory of Reproducing Kernels


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