English

On Efficient Distance Approximation for Graph Properties

Combinatorics 2020-01-07 v1 Data Structures and Algorithms

Abstract

A distance-approximation algorithm for a graph property P\mathcal{P} in the adjacency-matrix model is given an approximation parameter ϵ(0,1)\epsilon \in (0,1) and query access to the adjacency matrix of a graph G=(V,E)G=(V,E). It is required to output an estimate of the \emph{distance} between GG and the closest graph G=(V,E)G'=(V,E') that satisfies P\mathcal{P}, where the distance between graphs is the size of the symmetric difference between their edge sets, normalized by V2|V|^2. In this work we introduce property covers, as a framework for using distance-approximation algorithms for "simple" properties to design distance-approximation. Applying this framework we present distance-approximation algorithms with poly(1/ϵ)poly(1/\epsilon) query complexity for induced P3P_3-freeness, induced P4P_4-freeness, and Chordality. For induced C4C_4-freeness our algorithm has query complexity exp(poly(1/ϵ))exp(poly(1/\epsilon)). These complexities essentially match the corresponding known results for testing these properties and provide an exponential improvement on previously known results.

Keywords

Cite

@article{arxiv.2001.01452,
  title  = {On Efficient Distance Approximation for Graph Properties},
  author = {Nimrod Fiat and Dana Ron},
  journal= {arXiv preprint arXiv:2001.01452},
  year   = {2020}
}
R2 v1 2026-06-23T13:03:38.589Z