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arXiv 1306.0649cs.CC
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从可测仿射不变性质估计距离

Estimating the distance from testable affine-invariant properties

Hamed Hatami, Shachar Lovett

摘要:

设$\cal{P}$是函数$\mathbb{F}_p^n \to [R]$对于固定$p$和$R$的仿射不变性质。我们表明,如果$\cal{P}$是本地可测试的一个常数数量的查询,然后可以估计的距离从$\cal{P}$的查询的一个函数$f$。这是以前未知的,即使是简单的性质,如三次多项式在$\mathbb{F}_2$。我们的测试很简单:把$f$限制到一个常维仿射子空间,并测量它到$\cal{P}$的距离。我们表明,通过选择足够大的尺寸,这近似与高概率的全球距离的$f$从$\cP$。该分析结合了Fischer和Newman [SIAM J. Comp 2007]的方法,他们为图形属性建立了类似的结果,并结合了最近开发的高阶傅立叶分析工具,特别是Bhattacharyya等人[STOC 2013]开发的工具。

英文摘要:

Let $\cal{P}$ be an affine invariant property of functions $\mathbb{F}_p^n \to [R]$ for fixed $p$ and $R$. We show that if $\cal{P}$ is locally testable with a constant number of queries, then one can estimate the distance of a function $f$ from $\cal{P}$ with a constant number of queries. This was previously unknown even for simple properties such as cubic polynomials over $\mathbb{F}_2$. Our test is simple: take a restriction of $f$ to a constant dimensional affine subspace, and measure its distance from $\cal{P}$. We show that by choosing the dimension large enough, this approximates with high probability the global distance of $f$ from $\cP$. The analysis combines the approach of Fischer and Newman [SIAM J. Comp 2007] who established a similar result for graph properties, with recently developed tools in higher order Fourier analysis, in particular those developed in Bhattacharyya et al. [STOC 2013].

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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