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Approximate line nearest neighbor in high dimensions

机译:高维线上近似的近似线

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摘要

We consider the problem of approximate nearest neighbors in high dimensions, when the queries are lines. In this problem, given n points in Rd, we want to construct a data structure to support efficiently the following queries: given a line L, report the point p closest to L. This problem generalizes the more familiar nearest neighbor problem. From a practical perspective, lines, and low-dimensional flats in general, may model data under linear variation, such as physical objects under different lighting.
机译:当查询是线时,我们考虑在高维中近似最近的邻居的问题。在此问题中,给定Rd中的n个点,我们想构造一个数据结构以有效支持以下查询:给定一条线L,报告最接近L的点p。此问题概括了更熟悉的最近邻居问题。从实践的角度来看,直线和低维平面通常可以在线性变化下对数据建模,例如在不同光照下的物理对象。

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