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arXiv 2005.05812math.COcs.LG
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使用机器学习估计Cheeger常数

Estimating the Cheeger constant using machine learning

Indian Institute of Science Education and Research Bhopal(印度科学教育与研究学院博帕尔分院)

Ambar Jain, Shivam Pal, Kashyap Rajeevsarathy

摘要:

本文利用机器学习证明了连通正则图的Cheeger常数对图谱的最大两个特征值具有显著的线性依赖性。我们还表明,在较小尺寸的图上训练的深度神经网络可以用作估计较大图的Cheeger常数的有效估计器。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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