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  • 标题:Fourier Sparsity and Dimension
  • 本地全文:下载
  • 作者:Swagato Sanyal
  • 期刊名称:Theory of Computing
  • 印刷版ISSN:1557-2862
  • 电子版ISSN:1557-2862
  • 出版年度:2019
  • 卷号:15
  • 页码:1-13
  • DOI:10.4086/toc.2019.v015a011
  • 出版社:University of Chicago
  • 摘要:We prove that the Fourier dimension of any Boolean function with Fourier sparsity s is at most O( √ slogs). This bound is tight up to a factor of O(logs) since the Fourier dimension and sparsity of the address function are quadratically related. We obtain our result by bounding the non-adaptive parity decision tree complexity, which is known to be equivalent to the Fourier dimension. A consequence of our result is that any XOR function has a protocol of complexity O( √ rlogr) in the simultaneous communication model, where r is the rank of its communication matrix.
  • 关键词:Boolean functions; Fourier analysis; Boolean complexity; decision tree; query; complexity
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