超越talagand函数:检验单调性和单调性的新下界

Xi Chen, Erik Waingarten, Jinyu Xie
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引用次数: 42

摘要

我们证明了任意检验未知布尔函数f:{0,1}n→{0,1}是否为单调与远非单调的双边自适应算法查询复杂度的下界Ω(n1/3)。这改进了最近Belovs和Blais (STOC'16)对相同问题的Ω(n /4)的下界。我们的结果建立在一组新的随机布尔函数的基础上,这些随机布尔函数可以看作是Talagrand随机dnf的两级扩展。除了单调性之外,我们证明了双面自适应算法的下界Ω(√n)和单面非自适应算法的下界Ω(n),用于测试单调性,这是单调性的自然推广。后者与Khot和Shinkar (RANDOM'16)以及Baleshzar、Chakrabarty、Pallavoor、Raskhodnikova和Seshadhri(2017)的线性上界相匹配。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Beyond Talagrand functions: new lower bounds for testing monotonicity and unateness
We prove a lower bound of Ω(n1/3) for the query complexity of any two-sided and adaptive algorithm that tests whether an unknown Boolean function f:{0,1}n→ {0,1} is monotone versus far from monotone. This improves the recent lower bound of Ω(n1/4) for the same problem by Belovs and Blais (STOC'16). Our result builds on a new family of random Boolean functions that can be viewed as a two-level extension of Talagrand's random DNFs. Beyond monotonicity we prove a lower bound of Ω(√n) for two-sided, adaptive algorithms and a lower bound of Ω(n) for one-sided, non-adaptive algorithms for testing unateness, a natural generalization of monotonicity. The latter matches the linear upper bounds by Khot and Shinkar (RANDOM'16) and by Baleshzar, Chakrabarty, Pallavoor, Raskhodnikova, and Seshadhri (2017).
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