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arXiv 1407.3500cs.CC
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布尔函数Fourier维数的次线性上界

Sub-linear Upper Bounds on Fourier dimension of Boolean Functions in terms of Fourier sparsity

Swagato Sanyal

摘要:

证明了具有傅立叶稀疏性$s$的布尔函数的傅立叶维数至多为$O\left(s^{2/3}\right)$。我们的证明方法得到了一个改进的$\widetilde{O}(\sqrt{s})$的界假设Tsang~ \etal ~ \cite{tsang}的猜想,即对于每个稀疏$s$的布尔函数,都有一个$\mathbb{F}_2^n$的余维$O(\poly\log s)$的仿射子空间,该函数被限制在该子空间上。由于地址函数的傅立叶维数和稀疏性是二次分离的,因此该约束紧到多对数因子。我们通过观察布尔函数的傅立叶维数等价于其非自适应奇偶校验决策树复杂度,然后对后者进行界定,从而获得这些界限。

英文摘要:

We prove that the Fourier dimension of any Boolean function with Fourier sparsity $s$ is at most $O\left(s^{2/3}\right)$. Our proof method yields an improved bound of $\widetilde{O}(\sqrt{s})$ assuming a conjecture of Tsang~\etal~\cite{tsang}, that for every Boolean function of sparsity $s$ there is an affine subspace of $\mathbb{F}_2^n$ of co-dimension $O(\poly\log s)$ restricted to which the function is constant. This conjectured bound is tight upto poly-logarithmic factors as the Fourier dimension and sparsity of the address function are quadratically separated. We obtain these bounds by observing that the Fourier dimension of a Boolean function is equivalent to its non-adaptive parity decision tree complexity, and then bounding the latter.

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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