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Two-Sided Error Proximity Oblivious Testing

机译:双向误差近似测试

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摘要

Loosely speaking, a proximity-oblivious (property) tester is a randomized algorithm that makes a constant number of queries to a tested object and distinguishes objects that have a predetermined prop-erty from those that lack it. Specifically, for some threshold probability c, objects having the property are accepted with probability at least c, whereas objects that are ∈-far from having the property are accepted with probability at most c - F(∈), where F : (0,1] -> (0,1] is some fixed monotone function. (We stress that, in contrast to standard testers, a proximity-oblivious tester is not given the proximity parameter.) The foregoing notion, introduced by Goldreich and Ron (STOC 2009), was originally defined with respect to c = 1, which corresponds to onesided error (proximity-oblivious) testing. Here we study the two-sided error version of proximity-oblivious testers; that is, the (general) case of arbitrary c ∈ (0,1]. We show that, in many natural cases, two-sided error proximity-oblivious testers are more powerful than one-sided error proximity-oblivious testers; that is, many natural properties that have no one-sided error proximity-oblivious testers do have a two-sided error proximity-oblivious tester.
机译:松散地说,接近性(属性)测试器是一种随机算法,该算法对被测对象进行恒定数量的查询,并将具有预定属性的对象与没有该属性的对象区分开。具体来说,对于某个阈值概率c,具有该属性的对象被接受的概率至少为c,而与该属性相距∈远的对象被接受的概率最大为c-F(∈),其中F:(0, 1]->(0,1]是一些固定的单调函数。(我们强调,与标准测试仪相比,没有给近似值测试仪提供接近参数。)上述概念由Goldreich和Ron(STOC)提出。 (2009),最初是针对c = 1定义的,它对应于单边错误(接近度)测试。在这里,我们研究了无接近度测试器的两侧错误版本;即任意情况下的(一般)情况c∈(0,1]。我们证明,在许多自然情况下,双面误差非接近性测试器要比一侧误差非接近性测试器更强大;也就是说,许多没有单侧误差的自然特性错误接近度测试仪确实有一个双面错误接近度测试仪。

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