On Detection and Structural Reconstruction of Small-World Random Networks
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Abstract (arXiv)
In this paper, we study detection and fast reconstruction of the celebrated Watts-Strogatz (WS) small-world random graph model citepwatts1998collective which aims to describe real-world complex networks that exhibit both high clustering and short average length properties. The WS model with neighborhood size k and rewiring probability probability β can be viewed as a continuous interpolation between a deterministic ring lattice graph and the ErdHos-R'enyi random graph. We study both the computational and statistical aspects of detecting the deterministic ring lattice structure (or local geographical links, strong ties) in the presence of random connections (or long range links, weak ties), and for its recovery. The phase diagram in terms of (k,β) is partitioned into several regions according to the difficulty of the problem. We propose distinct methods for the various regions.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Apr 2016.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1.
3 papers.
- 2021Random Graph Matching with Improved Noise Robustnesscited by 16
- 2023Detection-Recovery Gap for Planted Dense Cyclescited by 4
- 2024Information-Theoretic Thresholds for Planted Dense Cyclescited by 2
- 2024Information-Theoretic Thresholds for Planted Dense Cycles1 Feb 2024
- 2023Detection-Recovery Gap for Planted Dense Cycles13 Feb 2023
- 2021Random Graph Matching with Improved Noise Robustness28 Jan 2021