Covers the proof of the Bourgain's ARV Theorem, focusing on the finite set of points in a semi-metric space and the application of the ARV algorithm to find the sparsest cut in a graph.
Covers polynomial identity testing using oracles and random point evaluation, with applications in graph theory and algorithmic aspects.
Explores Belief Propagation in graphical models, factor graphs, spin glass examples, Boltzmann distributions, and graph coloring properties.
Explores belief propagation on graphs, emphasizing normalization, recursive relations, and iterative computation of the partition function.
Explores distances on graphs, cut norms, spanning trees, blockmodels, metrics, norms, and ERGMs in network data analysis.
Covers the basics of information theory, entropy, and fixed points in graph colorings and the Ising model.
