近似最近邻搜索的硬度

A. Rubinstein
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引用次数: 90

摘要

我们证明了具有欧几里得、曼哈顿、汉明或编辑距离的近似双色最接近对的条件近二次运行时间下界。特别地,除非强指数时间假设(SETH)是假的,对于每一个δ>0存在一个ε>0的常数,使得计算双色最接近对的(1+ε)-近似需要Ω(n2−δ)时间。特别是,这意味着近似最近邻搜索的近似线性查询时间与多项式预处理时间。我们的约简使用了最近引入的分布式PCP框架,但使用代数几何(AG)代码获得了更高的效率。以前已经在其他设置中构建了AG规范的高效pcp,但我们的构建是第一个产生新的硬度结果的。
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Hardness of approximate nearest neighbor search
We prove conditional near-quadratic running time lower bounds for approximate Bichromatic Closest Pair with Euclidean, Manhattan, Hamming, or edit distance. Specifically, unless the Strong Exponential Time Hypothesis (SETH) is false, for every δ>0 there exists a constant ε>0 such that computing a (1+ε)-approximation to the Bichromatic Closest Pair requires Ω(n2−δ) time. In particular, this implies a near-linear query time for Approximate Nearest Neighbor search with polynomial preprocessing time. Our reduction uses the recently introduced Distributed PCP framework, but obtains improved efficiency using Algebraic Geometry (AG) codes. Efficient PCPs from AG codes have been constructed in other settings before, but our construction is the first to yield new hardness results.
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