Locality Sensitive Hashing for p-Exponential Kernels with Applications to Density Estimation
Barak Gorodissky ⋅ Tal Wagner
Abstract
A kernel $k(x,y)$ is *LSHable* if there exists a locality sensitive hashing scheme $\mathcal H$ such that $k(x,y)=\Pr_{h\sim\mathcal H}[h(x)=h(y)]$ for all $x,y$. This notion plays a key role in efficient kernel methods in high dimensions. In this work, we show that the $p$-exponential kernel $k(x,y)=\exp(-\lVert x-y \rVert_p)$ is LSHable in bounded regions for all $1
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