ML Anthology

The Cross Entropy Method for Classification

Shie Mannor, Dori Peleg, Reuven Y. Rubinstein
ICML 2005 pp. 561-568
doi:10.1145/1102351.1102422 /icml/2005/mannor2005icml-cross/

Abstract

We consider support vector machines for binary classification. As opposed to most approaches we use the number of support vectors (the "L0 norm") as a regularizing term instead of the L1 or L2 norms. In order to solve the optimization problem we use the cross entropy method to search over the possible sets of support vectors. The algorithm consists of solving a sequence of efficient linear programs. We report experiments where our method produces generalization errors that are similar to support vector machines, while using a considerably smaller number of support vectors.

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Text

Mannor et al. "The Cross Entropy Method for Classification." International Conference on Machine Learning, 2005. doi:10.1145/1102351.1102422

Markdown

[Mannor et al. "The Cross Entropy Method for Classification." International Conference on Machine Learning, 2005.](https://mlanthology.org/icml/2005/mannor2005icml-cross/) doi:10.1145/1102351.1102422

BibTeX

@inproceedings{mannor2005icml-cross,
  title     = {{The Cross Entropy Method for Classification}},
  author    = {Mannor, Shie and Peleg, Dori and Rubinstein, Reuven Y.},
  booktitle = {International Conference on Machine Learning},
  year      = {2005},
  pages     = {561-568},
  doi       = {10.1145/1102351.1102422},
  url       = {https://mlanthology.org/icml/2005/mannor2005icml-cross/}
}