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Testing symmetric properties of distributions

机译:测试分布的对称属性

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We introduce the notion of a canonical tester for a class of properties on distributions, that is, a tester strong and general enough that ~"a distribution property in the class is testable if and only if the canonical tester tests it.~" We construct a canonical tester for the class of properties of one or two distributions that are symmetric and satisfy a certain weak continuity condition. Analyzing the performance of the canonical tester on specific properties resolves two open problems, establishing lower bounds that match known upper bounds: we show that distinguishing between entropy < α or > β on distributions over [n] requires n ~(α/β-o(1)) samples, and distinguishing whether a pair of distributions has statistical distance < α or > β requires n ~(1-o(1)) samples. Our techniques also resolve a conjecture about a property that our canonical tester does not apply to: distinguishing identical distributions from those with statistical distance > 1/2 requires Ω(n ~(2/3)) samples.
机译:我们针对分布上的一类属性引入了规范测试器的概念,即,一种强大而通用的测试器,使得“只有当规范测试器对其进行测试时,该类中的分布属性才可以测试。”一个标准的测试器,用于测试一个或两个对称且满足一定弱连续性条件的分布的属性类别。分析规范测试器在特定属性上的性能可解决两个未解决的问题,建立与已知上限匹配的下限:我们表明,要区分[n]分布上的熵<α或>β,需要n〜(α/β-o (1))样本,并区分一对分布是否具有统计距离<α或>β,需要n〜(1-o(1))个样本。我们的技术还解决了一个关于我们的规范测试仪不适用的属性的猜想:将相同分布与统计距离> 1/2的分布区分开需要Ω(n〜(2/3))个样本。

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