ML Anthology

Approximate Analytical Bootstrap Averages for Support Vector Classifiers

Dörthe Malzahn, Manfred Opper
NeurIPS 2003 pp. 1189-1196
/neurips/2003/malzahn2003neurips-approximate/

Abstract

We compute approximate analytical bootstrap averages for support vec- tor classification using a combination of the replica method of statistical physics and the TAP approach for approximate inference. We test our method on a few datasets and compare it with exact averages obtained by extensive Monte-Carlo sampling.

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Cite

Text

Malzahn and Opper. "Approximate Analytical Bootstrap Averages for Support Vector Classifiers." Neural Information Processing Systems, 2003.

Markdown

[Malzahn and Opper. "Approximate Analytical Bootstrap Averages for Support Vector Classifiers." Neural Information Processing Systems, 2003.](https://mlanthology.org/neurips/2003/malzahn2003neurips-approximate/)

BibTeX

@inproceedings{malzahn2003neurips-approximate,
  title     = {{Approximate Analytical Bootstrap Averages for Support Vector Classifiers}},
  author    = {Malzahn, Dörthe and Opper, Manfred},
  booktitle = {Neural Information Processing Systems},
  year      = {2003},
  pages     = {1189-1196},
  url       = {https://mlanthology.org/neurips/2003/malzahn2003neurips-approximate/}
}