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New Research Explores Entropy Bounds in Graphon Models

By PulseAugur Editorial · [1 sources] ·

Connor Loehde-Woolard has published a new paper on arXiv detailing explicit bounds for the entropy of piecewise Hölder continuous graphon models. The research presents a result on the convergence rate of normalized entropy as graph size increases, with detailed proofs available in the appendix. This work derives quantitative bounds for the stochastic block model and random geometric graph model, offering explicit formulas rather than asymptotic statements. AI

IMPACT This research contributes to the theoretical understanding of graph models, which can have downstream applications in machine learning and data analysis.

RANK_REASON The cluster contains a new academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv stat.ML →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New Research Explores Entropy Bounds in Graphon Models

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The cluster contains a new academic paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.7]
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COVERAGE [1]

  1. arXiv stat.ML TIER_1 English(EN) · Connor Loehde-Woolard, Fran\c{c}ois G. Meyer ·

    Explicit Bounds on the Entropy of Piecewise H\"{o}lder Graphon Models

    arXiv:2608.26501v1 Announce Type: cross Abstract: We study the entropy of random graphs generated by piecewise H\"{o}lder continuous graphons. We first present a result on the rate of convergence of the normalized entropy as the size of the graph grows. The core ideas of the proo…

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