Almost optimal distribution-free sample-based testing of k-modality

Dana Ron, Asaf Rosin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For an integer k ≥ 0, a sequence σ = σ1,..., σn over a fully ordered set is k-modal, if there exist indices 1 = a0 < a1 < · · · < ak+1 = n such that for each i, the subsequence σai,..., σai+1 is either monotonically non-decreasing or monotonically non-increasing. The property of k-modality is a natural extension of monotonicity, which has been studied extensively in the area of property testing. We study one-sided error property testing of k-modality in the distribution-free sample-based model. We prove an upper bound of1 O (√kn log k/ε) on the sample complexity, and an almost matching lower bound of Ω (√kn/ε). When the underlying distribution is uniform, we obtain a completely tight bound of Θ (√kn/ε), which generalizes what is known for sample-based testing of monotonicity under the uniform distribution.

Original languageEnglish
Title of host publicationApproximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques, APPROX/RANDOM 2020
EditorsJaroslaw Byrka, Raghu Meka
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959771641
DOIs
StatePublished - 1 Aug 2020
Event23rd International Conference on Approximation Algorithms for Combinatorial Optimization Problems and 24th International Conference on Randomization and Computation, APPROX/RANDOM 2020 - Virtual, Online, United States
Duration: 17 Aug 202019 Aug 2020

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume176
ISSN (Print)1868-8969

Conference

Conference23rd International Conference on Approximation Algorithms for Combinatorial Optimization Problems and 24th International Conference on Randomization and Computation, APPROX/RANDOM 2020
Country/TerritoryUnited States
CityVirtual, Online
Period17/08/2019/08/20

Keywords

  • Distribution-free property testing
  • K-modality
  • Sample-based property testing

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