Testing Cluster Structure of Graphs
Not on the map. Why?
Abstract (arXiv)
We study the problem of recognizing the cluster structure of a graph in the framework of property testing in the bounded degree model. Given a parameter varepsilon, a d-bounded degree graph is defined to be (k, φ)-clusterable, if it can be partitioned into no more than k parts, such that the (inner) conductance of the induced subgraph on each part is at least φ and the (outer) conductance of each part is at most cd,kvarepsilon4φ2, where cd,k depends only on d,k. Our main result is a sublinear algorithm with the running time widetildeO(√n·poly(φ,k,1/varepsilon)) that takes as input a graph with maximum degree bounded by d, parameters k, φ, varepsilon, and with probability at least frac23, accepts the graph if it is (k,φ)-clusterable and rejects the graph if it is varepsilon-far from (k, φ^*)-clusterable for φ^* = c'd,kfracφ2 varepsilon4log n, where c'd,k depends only on d,k. By the lower bound of Omega(√n) on the number of queries needed for testing graph expansion, which corresponds to k=1 in our problem, our algorithm is asymptotically optimal up to polylogarithmic factors.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Apr 2015.
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Citing papers per year: 2021: 1; 2022: 3; 2023: 1; 2024: 1; 2025: 1.
7 papers.
- 2022A Tighter Analysis of Spectral Clustering, and Beyondcited by 13
- 2021Efficient and Local Parallel Random Walkscited by 2
- 2022Sublinear-Time Clustering Oracle for Signed Graphscited by 2
- 2022Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimationcited by 2
- 2024A Differentially Private Clustering Algorithm for Well-Clustered Graphscited by 2
- 2025Structure-Aware Spectral Sparsification via Uniform Edge Samplingcited by 1
- 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Timecited by 0
- 2025Structure-Aware Spectral Sparsification via Uniform Edge Sampling14 Oct 2025
- 2024A Differentially Private Clustering Algorithm for Well-Clustered Graphs21 Mar 2024
- 2023A Sublinear-Time Spectral Clustering Oracle with Improved Preprocessing Time27 Oct 2023
- 2022Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation1 Dec 2022
- 2022A Tighter Analysis of Spectral Clustering, and Beyond2 Aug 2022
- 2022Sublinear-Time Clustering Oracle for Signed Graphs28 Jun 2022
- 2021Efficient and Local Parallel Random Walks1 Dec 2021