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Distribution-Free Property Testing

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2764))

Abstract

We consider the problem of distribution-free property testing of functions. In this setting of property testing, the distance between functions is measured with respect to a fixed but unknown distribution D on the domain, and the testing algorithms have an oracle access to random sampling from the domain according to this distribution D. This notion of distribution-free testing was previously defined, but no distribution-free property testing algorithm was known for any (non-trivial) property. By extending known results (from “standard”, uniform distribution property testing), we present the first such distribution-free algorithms for two of the central problems in this field:

  • A distribution-free testing algorithm for low-degree multivariate polynomials with query complexity O(d 2 + d · ε − 1), where d is the total degree of the polynomial.

  • A distribution-free monotonicity testing algorithm for functions f:[n]dA for low-dimensions (e.g., when d is a constant) with query complexity \(O(\frac{\log^d n \cdot 2^d}{\epsilon})\).

The same approach that is taken for the distribution-free testing of low-degree polynomials is shown to apply also to several other problems.

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Halevy, S., Kushilevitz, E. (2003). Distribution-Free Property Testing. In: Arora, S., Jansen, K., Rolim, J.D.P., Sahai, A. (eds) Approximation, Randomization, and Combinatorial Optimization.. Algorithms and Techniques. RANDOM APPROX 2003 2003. Lecture Notes in Computer Science, vol 2764. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45198-3_26

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  • DOI: https://doi.org/10.1007/978-3-540-45198-3_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40770-6

  • Online ISBN: 978-3-540-45198-3

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