AI & ML
Explicit Bounds on the Entropy of Piecewise H\"{o}lder Graphon Models
arXiv stat.ML0 views
arXiv:2608.26501v2 Announce Type: replace-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 proof are described, with the detailed proof provided in the appendix. From this result, we then derive quantitative bounds on the entropy for the stochastic block model and random geometric graph model. These bounds provide explicit formulae rather than asymptotic statements which have been found previously.
Source：https://arxiv.org/abs/2608.26501PreviousK\"ahler landscapes for complex neural network descents and guarantees including a search and destroy of the Calabi-Yau manifoldNextMeasuring Learned Monotone Temporal Aggregation at Matched Admissibility
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