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  • 标题:Optimal bounds for monotonicity and Lipschitz testing over the hypercube
  • 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:2012
  • 卷号:2012
  • 出版社:Universität Trier, Lehrstuhl für Theoretische Computer-Forschung
  • 摘要:The problem of monotonicity testing of the boolean hypercube is a classic well-studied, yet unsolved question in property testing. We are given query access to f:01nR (for some ordered range R). The boolean hypercube n has a natural partial order, denoted by (defined by the product of coordinate-wise ordering). A function is \emph{monotone} if all pairs xy in n, f(x)f(y). The distance to monotonicity, f, is the minimum fraction of values of f that need to be changed to make f monotone. It is known that the edge tester using O(nlogR) samples can distinguish a monotone function from one where f. On the other hand, the best lower bound for monotonicity testing is min(R2n) . This leaves a quadratic gap in our knowledge, since R can be 2n.
  • 关键词:Monotonicity, Property Testing
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