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  • 标题:Testing $k$-Monotonicity: The Rise and Fall of Boolean Functions
  • 本地全文:下载
  • 作者:Clément L. Canonne ; Elena Grigorescu ; Siyao Guo
  • 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:1-55
  • DOI:10.4086/toc.2019.v015a001
  • 出版社:University of Chicago
  • 摘要:A Boolean k-monotone function defined over a finite poset domain D alternates between the values 0 and 1 at most k times on any ascending chain in D. Therefore, kmonotone functions are natural generalizations of the classical monotone functions, which are the 1-monotone functions. Motivated by the recent interest in k-monotone functions in the context of circuit complexity and learning theory, and by the central role that monotonicity testing plays in the context of property testing, we initiate a systematic study of k-monotone functions, in the property testing model. In this model, the goal is to distinguish functions that are k-monotone (or are close to being k-monotone) from functions that are far from being k-monotone. Our results include the following.
  • 关键词:property testing; Boolean functions; monotonicity; learning
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