使用机器学习估计Cheeger常数
Estimating the Cheeger constant using machine learning
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。