arXiv stat.ML
· Papers
Spectral Embeddings of Degree-$alpha$ Laplacians in Random Dot Product Graphs
arXiv:2608.10845v1 Announce Type: new Abstract: Spectral clustering methods for network data are commonly based on a few matrix representations, such as the adjacency matrix and the symmetric Laplacian. We study a continuum of degree-normalized spectral embeddings that includes these commonly used choices as special ca