Large multi-class image categorization with ensembles of label trees

@article{Wang2013LargeMI,
  title={Large multi-class image categorization with ensembles of label trees},
  author={Yang Wang and David A. Forsyth},
  journal={2013 IEEE International Conference on Multimedia and Expo (ICME)},
  year={2013},
  pages={1-6}
}
We consider sublinear test-time algorithms for image categorization when the number of classes is very large. Our method builds upon the label tree approach proposed in [1], which decomposes the label set into a tree structure and classify a test example by traversing the tree. Even though this method achieves logarithmic run-time, its performance is limited by the fact that any errors made in an internal node of the tree cannot be recovered. In this paper, we propose label forests - ensembles… CONTINUE READING
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