Approximately Counting and Sampling Small Witnesses Using a Colorful Decision Oracle

Holger Dell, John Lapinskas, Kitty Meeks

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

Abstract

In this paper, we design efficient algorithms to approximately count the number of edges of a given k-hypergraph, and to sample an approximately uniform random edge. The hypergraph is not given explicitly, and can be accessed only through its colourful independence oracle: The colourful independence oracle returns yes or no depending on whether a given subset of the vertices contains an edge that is colourful with respect to a given vertex-colouring. Our results extend and/or strengthen recent results in the graph oracle literature due to Beame et al. (ITCS 2018), Dell and Lapinskas (STOC 2018), and Bhattacharya et al. (ISAAC 2019). Our results have consequences for approximate counting/sampling: We can turn certain kinds of decision algorithms into approximate counting/sampling algorithms without causing much overhead in the running time. We apply this approximate-counting/sampling-to-decision reduction to key problems in fine-grained complexity (such as k-SUM, k-OV and weighted k-Clique) and parameterised complexity (such as induced subgraphs of size k or weight-k solutions to CSPs).
Original languageEnglish
JournalS I A M Journal on Computing
Volume51
Issue number4
Pages (from-to)849-899
ISSN0097-5397
DOIs
Publication statusPublished - 5 Jul 2022

Keywords

  • k-hypergraph
  • colourful independence oracle
  • approximate counting
  • uniform edge sampling
  • fine-grained complexity

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