Practical and Optimal LSH for Angular Distance

NeurIPS 2015 Alexandr AndoniPiotr IndykThijs LaarhovenIlya RazenshteynLudwig Schmidt

We show the existence of a Locality-Sensitive Hashing (LSH) family for the angular distance that yields an approximate Near Neighbor Search algorithm with the asymptotically optimal running time exponent. Unlike earlier algorithms with this property (e.g., Spherical LSH [Andoni, Indyk, Nguyen, Razenshteyn 2014], [Andoni, Razenshteyn 2015]), our algorithm is also practical, improving upon the well-studied hyperplane LSH [Charikar, 2002] in practice... (read more)

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