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  • 标题:An optimal lower bound for monotonicity testing over hypergrids
  • 本地全文:下载
  • 作者:Deeparnab Chakrabarty ; C. Seshadhri
  • 期刊名称:Electronic Colloquium on Computational Complexity
  • 印刷版ISSN:1433-8092
  • 出版年度:2013
  • 卷号:2013
  • 出版社:Universität Trier, Lehrstuhl für Theoretische Computer-Forschung
  • 摘要:

    For positive integers nd , consider the hypergrid [n]d with the coordinate-wise product partial ordering denoted by . A function f:[n]dN is monotone if xy, f(x)f(y).A function f is -far from monotone if at least an -fraction of values must be changed to makef monotone. Given a parameter , a \emph{monotonicity tester} must distinguish with high probability a monotone function from one that is -far.

    We prove that any (adaptive, two-sided) monotonicity tester for functions f:[n]dN must make(−1dlogn−−1log−1) queries. Recent upper bounds show the existence of O(−1dlogn)query monotonicity testers for hypergrids. This closes the question of monotonicity testing for hypergridsover arbitrary ranges. The previous best lower bound for general hypergrids was a non-adaptive boundof (dlogn).

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