The Power of Asymmetry in Binary Hashing
Abstract
When approximating binary similarity using the hamming distance between short binary hashes, we shown that even if the similarity is symmetric, we can have shorter and more accurate hashes by using two distinct code maps. I.e.~by approximating the similarity between $x$ and $x'$ as the hamming distance between $f(x)$ and $g(x')$, for two distinct binary codes $f,g$, rather than as the hamming distance between $f(x)$ and $f(x')$.
Cite
Text
Neyshabur et al. "The Power of Asymmetry in Binary Hashing." Neural Information Processing Systems, 2013.Markdown
[Neyshabur et al. "The Power of Asymmetry in Binary Hashing." Neural Information Processing Systems, 2013.](https://mlanthology.org/neurips/2013/neyshabur2013neurips-power/)BibTeX
@inproceedings{neyshabur2013neurips-power,
title = {{The Power of Asymmetry in Binary Hashing}},
author = {Neyshabur, Behnam and Srebro, Nati and Salakhutdinov, Ruslan and Makarychev, Yury and Yadollahpour, Payman},
booktitle = {Neural Information Processing Systems},
year = {2013},
pages = {2823-2831},
url = {https://mlanthology.org/neurips/2013/neyshabur2013neurips-power/}
}