English

The Power of Asymmetry in Binary Hashing

Machine Learning 2013-12-02 v1 Computer Vision and Pattern Recognition Information Retrieval

Abstract

When approximating binary similarity using the hamming distance between short binary hashes, we show 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 xx and xx' as the hamming distance between f(x)f(x) and g(x)g(x'), for two distinct binary codes f,gf,g, rather than as the hamming distance between f(x)f(x) and f(x)f(x').

Keywords

Cite

@article{arxiv.1311.7662,
  title  = {The Power of Asymmetry in Binary Hashing},
  author = {Behnam Neyshabur and Payman Yadollahpour and Yury Makarychev and Ruslan Salakhutdinov and Nathan Srebro},
  journal= {arXiv preprint arXiv:1311.7662},
  year   = {2013}
}

Comments

Accepted to NIPS 2013, 9 pages, 5 figures