English

$L_p$-Testers for Bounded Derivative Properties on Product Distributions

Data Structures and Algorithms 2014-05-02 v4

Abstract

We consider the problem of LpL_p-testing of class of bounded derivative properties over hypergrid domain with points distributed according to some product distribution. This class includes monotonicity, the Lipschitz property, (α,β)(\alpha,\beta)-generalized Lipschitz and many more properties. Previous results for LpL_p testing on [n]d[n]^d for this class were known for monotonicity and cc-Lipschitz properties over uniformly distributed domains. \medskip Our results imply testers that give the same upper bound for arbitrary product distributions as the hitherto known testers, which use uniformly randomly chosen samples from [n]d[n]^d, for monotonicity and Lipschitz testing. Also, our testers are \emph{optimal} for a large class of bounded derivative properties, that includes (α,β)(\alpha, \beta)-generalized Lipschitz property, over uniform distributions. Infact, each edge in [n]d[n]^d is allowed to have it's own left and right Lipschitz constants. The time complexity is \emph{same} for arbitrary product distributions.

Keywords

Cite

@article{arxiv.1404.5545,
  title  = {$L_p$-Testers for Bounded Derivative Properties on Product Distributions},
  author = {Kashyap Dixit},
  journal= {arXiv preprint arXiv:1404.5545},
  year   = {2014}
}
R2 v1 2026-06-22T03:55:54.915Z