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An Optimal Tester for k-Linear

机译:K-LINEAR的最佳测试仪

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A Boolean function f : t0, 1u n ? t0, 1u is k-linear if it returns the sum (over the binary field F2) of k coordinates of the input. In this paper, we study property testing of the classes k-Linear, the class of all k-linear functions, and k-Linear?, the class Yk j“0 j-Linear. We give a non-adaptive distribution-free two-sided -tester for k-Linear that makes O ? k log k ` 1 ˙ queries. This matches the lower bound known from the literature. We then give a non-adaptive distribution-free one-sided -tester for k-Linear? that makes the same number of queries and show that any non-adaptive uniform-distribution one-sided -tester for k-Linear must make at least ??pkqlog n ` ?p1{ q queries. The latter bound, almost matches the upper bound Opk log n ` 1{ q known from the literature. We then show that any adaptive uniform-distribution one-sided -tester for k-Linear must make at least ??p ? kqlog n ` ?p1{ q queries.
机译:布尔函数f:t0,1u n?如果它返回输入的k坐标的SUM(二进制字段F2),则T0,1U是k线性。在本文中,我们研究了k-linear的类的物业测试,所有k线性函数的类,以及k-linear?,类YK J“0 J-Linear。我们为k-linear提供一个非自适应的自适应分布双面 - Dester,使O? k log k`1¼查询。这与文献中已知的下限匹配。然后我们为K-linear提供无自适应的无自由分布单面 - 级别?这使得查询数量相同,并显示任何非自适应均匀分布的单面-Tester用于k-linear必须至少构成?? pkqlog n`?p1 {q查询。后者绑定,几乎与文献中已知的上限OPK log n`1 {q匹配。然后,我们表明,对于K-LINEAR的任何自适应均匀分布单侧 - 级别必须至少制作? kqlog n`?p1 {q查询。

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