Lecture
This lecture delves into the continued exploration of the stochastic blockmodel as a parametric generating mechanism, focusing on the normalized Laplacian matrix and its impact on eigenvalues. The discussion extends to the estimation of interactions and the challenges faced in spectral clustering. The lecture also covers non-parametric understanding of the blockmodel, graph limit functions, metrics, and norms for comparing graph models of different sizes.