Approximately Counting Triangles in Sublinear Time
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Abstract (arXiv)
We consider the problem of estimating the number of triangles in a graph. This problem has been extensively studied in both theory and practice, but all existing algorithms read the entire graph. In this work we design a em sublinear-time/ algorithm for approximating the number of triangles in a graph, where the algorithm is given query access to the graph. The allowed queries are degree queries, vertex-pair queries and neighbor queries. We show that for any given approximation parameter 0<ε<1, the algorithm provides an estimate widehatt such that with high constant probability, (1-ε)· t< widehatt<(1+ε)· t, where t is the number of triangles in the graph G. The expected query complexity of the algorithm is !left(fracnt1/3 + minleftm, fracm3/2trightright)· rm poly(log n, 1/ε), where n is the number of vertices in the graph and m is the number of edges, and the expected running time is !left(fracnt1/3 + fracm3/2tright)· rm poly(log n, 1/ε). We also prove that Omega!left(fracnt1/3 + minleftm, fracm3/2trightright) queries are necessary, thus establishing that the query complexity of this algorithm is optimal up to polylogarithmic factors in n (and the dependence on 1/ε).
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Apr 2015.
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Citing papers per year: 2022: 4; 2023: 0; 2024: 0; 2025: 1; 2026: 1.
6 papers.
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- 2022Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation1 Dec 2022
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- 2022Agent-based Graph Neural Networks22 Jun 2022
- 2022Degree-Preserving Randomized Response for Graph Neural Networks under Local Differential Privacy21 Feb 2022