ML Anthology

Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning

Dmitry Gavinsky
JMLR 2003 pp. 101-117
/jmlr/2003/gavinsky2003jmlr-optimallysmooth/

Abstract

We describe a new boosting algorithm that is the first such algorithm to be both smooth and adaptive. These two features make possible performance improvements for many learning tasks whose solutions use a boosting technique.

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Cite

Text

Gavinsky. "Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning." Journal of Machine Learning Research, 2003.

Markdown

[Gavinsky. "Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning." Journal of Machine Learning Research, 2003.](https://mlanthology.org/jmlr/2003/gavinsky2003jmlr-optimallysmooth/)

BibTeX

@article{gavinsky2003jmlr-optimallysmooth,
  title     = {{Optimally-Smooth Adaptive Boosting and Application to Agnostic Learning}},
  author    = {Gavinsky, Dmitry},
  journal   = {Journal of Machine Learning Research},
  year      = {2003},
  pages     = {101-117},
  volume    = {4},
  url       = {https://mlanthology.org/jmlr/2003/gavinsky2003jmlr-optimallysmooth/}
}