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Estimating the Cheeger constant using machine learning
Published 12 May 2020 in math.CO and cs.LG | (2005.05812v1)
Abstract: In this paper, we use machine learning to show that the Cheeger constant of a connected regular graph has a predominant linear dependence on the largest two eigenvalues of the graph spectrum. We also show that a trained deep neural network on graphs of smaller sizes can be used as an effective estimator in estimating the Cheeger constant of larger graphs.
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