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Research questionHow can spectral community detection in a two-community SBM approach information-theoretic error limits with less preprocessing?In this model, graph connectivity must reveal the two latent communities while spectral estimation remains accurate enough for near-optimal error rates. The adjacency matrix’s second eigenvector is central to the recovery signal, but simplifying the surrounding procedure can affect both accuracy and computational cost.
Machine Learning
Research Paper
Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.Simplify to Amplify: Achieving Information-Theoretic Bounds with Fewer Steps in Spectral Community DetectionApplies to a streamlined adjacency-matrix spectral procedure for the two-community SBM, with emphasis on the second eigenvector. The source supplies theoretical error analysis and experimental validation of its bounds and computational simplifications.research paper · Sep 3, 2026
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