Fast Supervised Hashing with Decision Trees for High-Dimensional Data

@article{Lin2014FastSH,
  title={Fast Supervised Hashing with Decision Trees for High-Dimensional Data},
  author={Guosheng Lin and Chunhua Shen and Qinfeng Shi and A. V. D. Hengel and D. Suter},
  journal={2014 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2014},
  pages={1971-1978}
}
  • Guosheng Lin, Chunhua Shen, +2 authors D. Suter
  • Published 2014
  • Computer Science
  • 2014 IEEE Conference on Computer Vision and Pattern Recognition
  • Supervised hashing aims to map the original features to compact binary codes that are able to preserve label based similarity in the Hamming space. Non-linear hash functions have demonstrated their advantage over linear ones due to their powerful generalization capability. In the literature, kernel functions are typically used to achieve non-linearity in hashing, which achieve encouraging retrieval perfor- mance at the price of slow evaluation and training time. Here we propose to use boosted… CONTINUE READING
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