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A Sub-linear Time Algorithm for Approximating k-Nearest-Neighbor with Full Quality Guarantee

机译:具有全质量保证的近似K离邻邻的子线性时间算法

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In this paper we propose an algorithm for the approximate k-Nearest-Neighbors problem. According to the existing researches, there are two kinds of approximation criteria. One is the distance criterion, and the other is the recall criterion. All former algorithms suffer the problem that there are no theoretical guarantees for the two approximation criteria. The algorithm proposed in this paper unifies the two kinds of approximation criteria, and has full theoretical guarantees. Furthermore, the query time of the algorithm is sub-linear. As far as we know, it is the first algorithm that achieves both sub-linear query time and full theoretical approximation guarantees.
机译:在本文中,我们提出了一种算法,用于近似的k离立邻居问题。 根据现有的研究,有两种近似标准。 一个是距离标准,另一个是召回标准。 所有以前的算法都存在对两个近似标准没有理论保证的问题。 本文提出的算法统一了两种近似标准,并具有完全理论担保。 此外,算法的查询时间是子线性的。 据我们所知,它是第一算法,实现了子线性查询时间和完全理论近似保证。

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