Spectral clustering in the Gaussian mixture block model

arXiv:2305.00979v2 Announce Type: replace
Abstract: Gaussian mixture block models are distributions over graphs that strive to model modern networks: to generate a graph from such a model, we associate each vertex $i$ with a latent feature vector $u_i \in \mathbb{R}^d$ sampled from a mixture of Gaussians, and we add edge $(i,j)$ if and only if the feature vectors are sufficiently similar, in that $\langle u_i,u_j \rangle \ge \tau$ for a pre-specified threshold $\tau$. The different components of the Gaussian mixture …

abstract arxiv block clustering cs.ds cs.si edge feature feature vector generate graph graphs math.pr math.st modern networks stat.ml stat.th type vector vertex