• DocumentCode
    655190
  • Title

    Estimating the Distance from Testable Affine-Invariant Properties

  • Author

    Hatami, Hamed ; Lovett, Shachar

  • Author_Institution
    Sch. of Comput. Sci., McGill Univ., Montreal, QC, Canada
  • fYear
    2013
  • fDate
    26-29 Oct. 2013
  • Firstpage
    237
  • Lastpage
    242
  • Abstract
    Let P be an affine invariant property of multivariate functions over a constant size finite field. We show that if P is locally testable with a constant number of queries, then one can estimate the distance of a function f from P with a constant number of queries. This was previously unknown even for simple properties such as cubic polynomials over the binary field. Our test is simple: take a restriction of f to a constant dimensional affine subspace, and measure its distance from P. We show that by choosing the dimension large enough, this approximates with high probability the global distance of f from P. The analysis combines the approach of Fischer and Newman [SIAM J. Comp 2007] who established a similar result for graph properties, with recently developed tools in higher order Fourier analysis, in particular those developed in Bhattacharyya et al. [STOC 2013].
  • Keywords
    Fourier analysis; affine transforms; graph theory; polynomials; probability; affine invariant property; binary field; constant dimensional affine subspace; constant size finite field; cubic polynomials; global distance; graph property; higher order Fourier analysis; multivariate functions; probability; testable affine-invariant property; Computer science; Correlation; Educational institutions; Frequency modulation; Polynomials; Probabilistic logic; Testing; affine invariant properties; higher-order fourier analysis; property testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Foundations of Computer Science (FOCS), 2013 IEEE 54th Annual Symposium on
  • Conference_Location
    Berkeley, CA
  • ISSN
    0272-5428
  • Type

    conf

  • DOI
    10.1109/FOCS.2013.33
  • Filename
    6686159