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2013 NeurIPS NeurIPS 2013

The Power of Asymmetry in Binary Hashing

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 $f(x')$.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Computer Science
📈 Trend Setter - Retrieval

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