Online Coordinate Boosting
Abstract
We present a new online boosting algorithm for updating the weights of a boosted classifier, which yields a closer approximation to the edges found by Freund and Schapire's AdaBoost algorithm than previous online boosting algorithms. We contribute a new way of deriving the online algorithm that ties together previous online boosting work. The online algorithm is derived by minimizing AdaBoost's loss as a single example is added to the training set. The equations show that the optimization is computationally expensive. However, a fast online approximation is possible. We compare approximation error to edges found by batch AdaBoost on synthetic datasets and generalization error on face datasets and the MNIST dataset.
Cite
Text
Pelossof et al. "Online Coordinate Boosting." IEEE/CVF International Conference on Computer Vision Workshops, 2009. doi:10.1109/ICCVW.2009.5457454Markdown
[Pelossof et al. "Online Coordinate Boosting." IEEE/CVF International Conference on Computer Vision Workshops, 2009.](https://mlanthology.org/iccvw/2009/pelossof2009iccvw-online/) doi:10.1109/ICCVW.2009.5457454BibTeX
@inproceedings{pelossof2009iccvw-online,
title = {{Online Coordinate Boosting}},
author = {Pelossof, Raphael and Jones, Michael and Vovsha, Ilia and Rudin, Cynthia},
booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
year = {2009},
pages = {1354-1361},
doi = {10.1109/ICCVW.2009.5457454},
url = {https://mlanthology.org/iccvw/2009/pelossof2009iccvw-online/}
}