A nearly quadratic bound for the decision tree complexity of k-SUM

Esther Ezra, Micha Sharir

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

Abstract

We show that the k-SUM problem can be solved by a linear decision tree of depth O(n2 log2 n), improving the recent bound O(n3 log3 n) of Cardinal et al. [7]. Our bound depends linearly on k, and allows us to conclude that the number of linear queries required to decide the n-dimensional KNAPSACK or SUBSETSUM problems is only O(n3 log n), improving the currently best known bounds by a factor of n [28, 29]. Our algorithm extends to the RAM model, showing that the k-SUM problem can be solved in expected polynomial time, for any fixed k, with the above bound on the number of linear queries. Our approach relies on a new point-location mechanism, exploiting "ϵ-cuttings" that are based on vertical decompositions in hyperplane arrangements in high dimensions. A major side result of the analysis in this paper is a sharper bound on the complexity of the vertical decomposition of such an arrangement (in terms of its dependence on the dimension). We hope that this study will reveal further structural properties of vertical decompositions in hyperplane arrangements.

Original languageEnglish
Title of host publication33rd International Symposium on Computational Geometry, SoCG 2017
EditorsMatthew J. Katz, Boris Aronov
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Pages411-4115
Number of pages3705
ISBN (Electronic)9783959770385
DOIs
StatePublished - 1 Jun 2017
Event33rd International Symposium on Computational Geometry, SoCG 2017 - Brisbane, Australia
Duration: 4 Jul 20177 Jul 2017

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume77

Conference

Conference33rd International Symposium on Computational Geometry, SoCG 2017
Country/TerritoryAustralia
CityBrisbane
Period4/07/177/07/17

Keywords

  • Hyperplane arrangements
  • K-SUM and k-LDT
  • Linear decision tree
  • Point-location
  • Vertical decompositions
  • ϵ-cuttings

All Science Journal Classification (ASJC) codes

  • Software

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