Another important focus has been on the normalized Laplacian spectrum, which is derived from the normalized Laplacian matrix of a graph. This spectrum is crucial for understanding the graph's ...

Abstract: We consider a general form of transductive learning on graphs with Laplacian regularization, and derive margin-based generalization bounds using appropriate geometric properties of the graph ...

For instance, one study examined the normalized Laplacian eigenvalues of power graphs associated with finite cyclic groups, providing a deeper understanding of how these graphs behave under ...

I explore the theoretical aspect of constructing a normalized Laplacian, as well as the impacts of different parameter choices on the segmentation. I find that spectral clustering can indeed ...