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arxiv: 1407.3500 · v1 · pith:L4GLZEU4new · submitted 2014-07-13 · 💻 cs.CC

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

classification 💻 cs.CC
keywords fourierfunctionbooleandimensionsparsityboundboundstsang
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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.

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