Predictable Dual-View Hashing

Mohammad Rastegari, Jonghyun Choi, Shobeir Fakhraei, Daume Hal, Larry Davis

ICML 2013 pp. 1328-1336

/icml/2013/rastegari2013icml-predictable/

Abstract

We propose a Predictable Dual-View Hashing (PDH) algorithm which embeds proximity of data samples in the original spaces. We create a cross-view hamming space with the ability to compare information from previously incomparable domains with a notion of ‘predictability’. By performing comparative experimental analysis on two large datasets, PASCAL-Sentence and SUN-Attribute, we demonstrate the superiority of our method to the state-of-the-art dual-view binary code learning algorithms.

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Cite

Text

Rastegari et al. "Predictable Dual-View Hashing." International Conference on Machine Learning, 2013.

Markdown

[Rastegari et al. "Predictable Dual-View Hashing." International Conference on Machine Learning, 2013.](https://mlanthology.org/icml/2013/rastegari2013icml-predictable/)

BibTeX

@inproceedings{rastegari2013icml-predictable,
  title     = {{Predictable Dual-View Hashing}},
  author    = {Rastegari, Mohammad and Choi, Jonghyun and Fakhraei, Shobeir and Hal, Daume and Davis, Larry},
  booktitle = {International Conference on Machine Learning},
  year      = {2013},
  pages     = {1328-1336},
  volume    = {28},
  url       = {https://mlanthology.org/icml/2013/rastegari2013icml-predictable/}
}