Lecture
This lecture by the instructor covers the definition of distances on graphs, including the edit distance and the Hamming distance. It explores the cut norm of graphs, the spanning tree dissimilarity, and the blockmodel. The lecture delves into metrics and norms, focusing on the Hamming distance, Jaccard distance, lp distances on eigenvalues, and the Steinhaus transform. It also discusses ERGMs, their applications in sociology, and the exponential random graph models. The content includes examples, definitions, theorems, and special cases related to network data analysis.