ML Anthology

Adaptivity to Local Smoothness and Dimension in Kernel Regression

Samory Kpotufe, Vikas Garg
NeurIPS 2013 pp. 3075-3083
/neurips/2013/kpotufe2013neurips-adaptivity/

Abstract

We present the first result for kernel regression where the procedure adapts locally at a point $x$ to both the unknown local dimension of the metric and the unknown H\older-continuity of the regression function at $x$. The result holds with high probability simultaneously at all points $x$ in a metric space of unknown structure."

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Cite

Text

Kpotufe and Garg. "Adaptivity to Local Smoothness and Dimension in Kernel Regression." Neural Information Processing Systems, 2013.

Markdown

[Kpotufe and Garg. "Adaptivity to Local Smoothness and Dimension in Kernel Regression." Neural Information Processing Systems, 2013.](https://mlanthology.org/neurips/2013/kpotufe2013neurips-adaptivity/)

BibTeX

@inproceedings{kpotufe2013neurips-adaptivity,
  title     = {{Adaptivity to Local Smoothness and Dimension in Kernel Regression}},
  author    = {Kpotufe, Samory and Garg, Vikas},
  booktitle = {Neural Information Processing Systems},
  year      = {2013},
  pages     = {3075-3083},
  url       = {https://mlanthology.org/neurips/2013/kpotufe2013neurips-adaptivity/}
}